Michael Dell, the founder of Dell Technologies Inc., shared his company’s quarterly earnings report dated July 31, 1984, saying, “This one page changed my life.” The billionaire said on his X post that the numbers on that piece of paper convinced his parents that they didn’t need to go back to college. He started the company in 1984, originally known as PC’s Limited, in his dorm room at the University of Texas at Austin, upgrading PCs and building clones of IBM PCs from stock parts.

As we see from his X post below, his venture seemed to be successful from the get-go, with Dell selling almost a million dollars’ worth of parts and computers, which resulted in a net income of $134,762.75 for just one quarter — equal to $433,150.05 in 2026 dollars. This is an achievement for any startup not backed by millions of dollars, much less by a 19-year-old college freshman backed by just $1,000, with the investment returning 13,500% in less than a year.

Dell went public four years after it was founded, but after a quarter of a century of being listed on the stock market, Michael Dell and Silver Lake Partners decided to take the company private again in 2013 in a $24.9 billion deal as it struggled with the rise of smartphones and tablets. After five years without mandatory quarterly reports, Dell decided to go public again, and it currently has a market capitalization of around $261.92 billion.

The fledgling dorm-room startup has turned from a niche supplier of off-brand IBM-compatible computers into a massive tech giant. It owns iconic computer brands like Alienware and XPS, and has also jumped on the AI bandwagon, supplying servers to hyperscalers and data centers. Its latest income statement also lists total net revenue of $43 billion and a net income of $3.4 billion. Dell’s risk in 1984 also paid handsomely for him. He’s currently the fifth richest person on Forbes’ real-time billionaires list, with a net worth of $229.2 billion.

The computer company has also had its fair share of controversies. This includes an SEC investigation into improper accounting practices in 2005, a lawsuit and massive recall related to laptop batteries catching fire in 2007, and a security vulnerability in 2015 that could have exposed customer data to bad actors. Despite all that, the company continues to thrive today and release new products like the $699 XPS 13 and an affordable OLED gaming monitor in the Alienware AW3426DW. Dell has made a significant impact on PCs, laptops, and other systems for gaming, productivity, enterprise, and more.

Microsoft said that it’s planning to optimize Windows 11 for systems with 8GB of RAM and above as part of its promise to improve Windows 11 in March 2026. The company said in its latest update that the optimization is part of expanding its focus on operating system upgrades, which include a faster out-of-the-box experience, easier parental controls, and improved voice interactions.

While the official minimum specifications for Windows 11 sit at just 4GB of RAM, most PC builders advise getting at least 16GB if you want to have a smooth experience. In fact, Microsoft has previously recommended 32GB of RAM for Windows 11 for gamers, especially if they want a system that can handle games in the near future. Unfortunately, the RAMpocalypse has forced both users and manufacturers to stick with slower DDR4 memory and lower capacities. Some experts predict that the entry-level PC will disappear by 2028, and we’ve even seen some manufacturers, including Apple, reintroduce 8GB laptops just to hit a specific price point.

The resurgence of 8GB systems will likely deliver a bad experience for users who stick with Windows 11, which is the likely reason why Microsoft is pushing for the optimization of its operating system. If Windows 11 performs poorly on these systems, it could draw users towards macOS or Linux alternatives as they blame the operating system for underperforming on limited hardware. In fact, we’ve already seen this happen before — after Microsoft ended support for Windows 10, MacBooks saw an uptick in sales as users migrated towards macOS instead of going for Windows 11. SteamOS is also encouraging some gamers to ditch Windows, and Valve is working on a general release for the OS, which many say contains less bloat and is a bit snappier than what Microsoft offers.

The RAM shortage crisis, alongside increasing competition, is forcing Microsoft to do better with Windows 11. Hopefully, these optimizations arrive sooner and don’t introduce new bugs, allowing both new and existing users to get more out of their systems.

The Windows blog post also gave an update on what improvements the company has made to Windows 11 so far. This includes a better Windows Search experience, more Taskbar and Start customizations, a more responsive and reliable File Explorer, among others. Many of these changes are still in preview, though, so unless you’re part of the Windows Insider Program, you’ll have to wait a few more weeks to months before you can start enjoying these changes.

Whether driven by a desire for transparency or to keep OpenAI from hogging the spotlight when it comes to advertising advanced AI models, Anthropic revealed that Claude also hacked into three production systems belonging to unsuspecting targets during cybersecurity capabilities testing. Two of the affected companies didn't know they had been hacked, while a third one is unreachable.

The alleged incidents reportedly happened during the previous quarter and involved several versions of Claude: Opus 4.7, Mythos 5, and "an internal research test model." Similar to what happened when OpenAI Sol hacked into Hugging Face, Anthropic was running Claude through cybersecurity capture-the-flag scenarios where the bot was told to find a piece of information somewhere in its network. Anthropic says there were 141,006 test runs, and the three incidents occurred over six problematic runs. As expected, the tests ran with most AI safeguards disabled.

The problem is, the network was not isolated, a newbie mistake that some might even find suspicious. This was due to an alleged "miscommunication" between Anthropic’s virtual test lab firm Irregular, which gave the bots full access to the internet. For safety's sake, the Claudes were apparently told they were in an isolated environment, which didn't help much.

The first time, Claude Opus 4.7 had to find a piece of data belonging to an imaginary company. As it turns out, there was actually a real company whose website domain matched the fake one. With internet access, it gained application and infrastructure credentials and grabbed "several hundred rows" of data from a production database.

For two out of four runs where hacking took place, Claude didn't see any problem and "rationalized that the real company must be part of the exercise," but soldiered on. The other two times, it just kept going. Anthropic notes this was the only case of the three where the bot continued to operate after the realization the company actually existed for the aforementioned reason. However, the firm's interpretation is open to discussion.

The second, and potentially more interesting, was a bona fide supply-chain attack, this time perpetrated by Mythos. The fake data available to the bot included an installation script for a hypothetical developer that included installing Python packages. Much like a human would, Claude noticed the obvious attack vector and, once again, due to having internet access, inferred that publishing a booby-trapped package in the PyPI repository would do the trick. Unfortunately, it was the real one that the whole world uses.

In speedrun form for brevity: Claude needed a PyPI account, meaning it needed an email and a phone number. It tried buying one but found itself short of both pockets and funds; but it found another free email provider without that requirement, registered the PyPI account, and uploaded a malware package to PyPI. The package was seemingly only up for one hour but was downloaded and run on 15 systems.

In a twist of irony, one such system belonged to a security vendor that scans PyPI for malware, and lo and behold, promptly failed to find Claude's booby-trap and ran it. Once Claude presumably had remote code execution privileges, it used the credentials it found for further infiltration. The amusing bit is that Claude had no idea this company existed and didn't target it; the downloads just happened because the package was up and live for a short while.

According to Anthropic, the bot did detect it was acting on the real internet and even said that publishing a package like this was "NOT okay." However, it talked itself into believing it was in a test environment as it didn't recognize the real SSL certificates for the connections. It even believed the 2026 calendar date on the systems "proved" the environment was staged. It even recognized the systems that installed the malware as part of the experiment.

As for the third incident, Anthropic isn't saying much, other than Claude scanned 9,000 real live potential alternative targets once it noticed the intended one wasn't reachable. One of them reportedly had a live page with debugging information and was vulnerable to plain ol' SQL injection. Interestingly, this time around, once Claude noticed that the servers it was accessing resided on a cloud environment and not on the local network, it stopped the attack.

For its part, Anthropic recognizes that despite Claude following the instructions for the objectives, the fact that it stopped by itself once it found the target was real in only one of the cases is food for some thought. The firm says it's talking to METR for a third-party review, and it needs to "better co-design evaluation environments."

Oddly enough, Anthropic believes Claude probably wouldn't have gone online "if the prompt had clearly explained which systems were in and out of scope for the evaluation," while also stating the incidents were "closer to a harness and operational failure than a model alignment failure."

Bondtech, the creator and manufacturer of the INDX toolchanger system used to create the highly anticipated Prusa CORE One+ INDX, admitted to a significant labeling mistake. The nozzles provided with the INDX kit do not meet industry standards for “hardened steel” as advertised.

The issue is not the nozzles themselves, which are made of nitrocarburized steel and are superior to the standard brass nozzles that come with a stock Prusa CORE One+. The problem is how they were labeled and the resulting customer expectations. If Bondtech said from the beginning (or before customers locked in their pre-orders) that the INDX shipped with ordinary steel nozzles, no one would have blinked.

Information on the nozzle quality began to surface after a Reddit user posted a support email from Bondtech founder, Martin Bondeus. The email stated that “during production, we encountered manufacturing challenges that prevented us from machining that material reliably – the cutting tools simply did not withstand the process. Rather than releasing a product with inconsistent quality, we decided to supply the nitrocarburized version for the time being.”

These nozzles are not of poor quality, but they fall short of the standards set for hardened steel. According to a statement by Bondtech, the Founders Edition, and the initial batches of Prusa CORE One+ INDX Upgrade Kit, shipped with nitrocarburized steel, which is steel treated to obtain a hard shell. They’ve batch tested the nozzles and found them to be around 30-32 on the Hardness Rockwell C scale (HRC). For comparison, true hardened steel lands at 55-60 while an everyday brass nozzle comes in under 10 HRC.

For most users, and most materials, these mid-tier steel nozzles work exceptionally well and will last for an extremely long time. But once you start to feed your INDX abrasive filaments like glass-fiber, carbon-fiber, glow in the dark and metal filled filaments, things get dicey. The treated steel nozzles will last longer than brass, but Bondtech said they will experience “accelerated wear” when printing abrasives.

Bondtech has stated on its website that a “concrete solution” to the problem is not ready and that manufacturing truly hardened INDX nozzles could take months. They are also not offering any form of compensation before knowing the cost of the replacements. They are requesting that customers hold off on returning the kits and simply enjoy using non-abrasive materials until a solution is found.

The INDX takes a bespoke induction heated nozzle that has no off the shelf replacement at this time.

The news has hit the Founders Edition buyers quite hard, as many have already found difficulty with the kits they so eagerly purchased months ago. Some assembly problems can be expected with such a product, as they are being mounted on CORE One printers already in service. The INDX is a separate upgrade kit, and it requires stripping down a CORE One, removing the Nextruder and replacing it with the INDX carriage, then mounting a rack to hold the eight tool heads.

One “founder” was so upset he vibe coded an entire website in protest: Nozzlegate.com. The website outlines what the perceived problems are with Bondtech, and what consumers can do about it. We contacted the website owner, who asked to go by his handle “Daddie0.”

He told me that, like others who purchased Founder Edition kits, he’s disappointed in the quality of the product. He said his INDX was suffering from multiple mid-print crashes and layer shifts, and after two weeks of troubleshooting, it was finally fixed with a firmware update from Prusa. “Then nozzlegate hits. My EU right-given two-week return window ends a day after the news breaks.”

Realizing that his window for a standard, hassle-free return had closed on a machine he felt was a lemon, he shifted strategies. He began digging into Bondtech’s official documentation to see what recourse he had for a defective product.

What he found sparked a new battle. Disagreeing with Bondtech’s listed 90-day warranty policy, which he claims misleads consumers by failing to mention Sweden's mandatory multi-year consumer protections, he channeled his frustration into the NozzleGate website.

We asked Prusa Research for a statement regarding the INDX nozzle debacle and were informed that they are as surprised as the rest of us and will issue a formal statement soon. The INDX kit is a collaboration between the two companies, with the first wave of Founders Edition kits a limited edition run going to early adopters.

Tom’s Hardware received a Founders Edition INDX kit, which we installed on a Prusa CORE One we previously reviewed. Though the build took over the kitchen table for an entire weekend, our resulting INDX is printing non-abrasive filaments with excellent quality.

Despite widespread public backlash, Sony has reaffirmed its plan to transition PlayStation to an all-digital platform during the company's FY26 Q1 earnings call. The company is moving forward with ending the production of physical game discs in January 2028. After this date, the company will no longer manufacture physical media for new game releases. This decision gives PlayStation fans and retailers a little over a year and a half to prepare for the change.

When asked about Sony's decision to end production of physical game discs during the Q&A session, Lin Tao, Executive Officer and CFO for Sony, replied that:

"On this point, we announced that January 2028 onwards, we will no longer be manufacturing game discs. One and a half years ahead. We made this announcement at this time. There are various reasons we made this decision."

Tao further explains the rationale behind the digital paradigm shift, a move that was met with negative criticism from PlayStation fans and parts of the industry.

"The biggest being that the digitalization of content overall has been progressing. That’s the big factor. It’s not just for PlayStation, but for all kinds of contents; digitalization is progressing. When we think about the future, we put in a lot of thought and time; we cautiously considered this, we came to this conclusion, we’re going to cautiously move this forward.

To this decision, we have received various opinions; people have strong views. We understand that the community has put forth those views to us.

Games are loved by many people. It’s a form of entertainment that’s loved by people; it’s connected to people’s fond memories in many cases. We understand those emotions. We want to consider that."

According to Sony's financial results for FY26 Q1, which covers the period from April to June, the company raked in $1.2 billion in digital game revenue. In stark contrast, physical game sales brought in only $128 million for Sony, meaning digital revenue was more than 9X higher than physical sales. The growth in digital sales and the disparity with physical sales shows why Sony is eager to go all in on digital.

Sony was asked directly about the impact of discontinuing physical discs. In response, Ishii, a Corporate Communications executive at the company, provided the following statement:

"Well, up until 2028, well, at this point in time, well, we are not seeing any impact on our business as of now. Going forward, about the content sales, I think a large part is already digitized.

Therefore, as a result of the discontinuation of a disc, we don’t see that there will be any negative impact on our business. However, as I already said, the users, the players, have attachments, and we have to think about how to respond to that feedback."

Phasing out game discs will undoubtedly have a significant financial impact on gamers. Physical game discs not only provide ownership, but they also come with the benefit of resale. Gamers can recoup some of what they paid for it once they are finished playing. The extinction of game discs represents the loss of the ability to share physical games with friends and family. The PlayStation platform does not support sharing digital games, unlike services like Valve’s Steam Families or Nintendo’s Virtual Game Cards.

Game discs enable gamers on a tight budget to purchase second-hand copies of games at great prices at their local game stores or online marketplaces. For instance, used copies of The Last of Us Part I, which came out four years ago, go for as little as $25, while the digital version remains priced at around $69.99 on the PlayStation Store. Even during major promotional events like Days of Play or Black Friday, digital discounts have rarely brought prices below $29.99. Second-hand physical copies are simply a more affordable choice for many players.

Without game discs, PlayStation console owners will have to rely more on internal storage, and when that depletes, they will have to expand the storage with the best PS5 SSDs. The issue is that SSDs are ludicrously expensive right now due to the storage shortage, which could last way beyond January 2028.

The discontinuation of physical discs does not just affect consumers but also retailers. However, Sony expects limited business impact in that aspect since the digital transition has somewhat started a long time ago. Tao elaborated, "For the last 30 years, we have been selling PlayStation, and the retail partners have always been important to us. With the completion of the disc production, we communicated this at an early stage so that we have enough time to be able to listen to various partners’ voices.”

Tao continued, “In North America, this has already happened, but without discs. In the package, there’s a code. That’s how they sell in North America. About the retailers, there are regional characteristics. For each regional partner, we try to have thorough dialogues so that we can end up in a win-win situation. Now, the differentiation from PC. We don’t feel that the disc is the factor to differentiate from the PC."

Gamers are actively voicing their opposition to Sony’s move away from physical media. DoesItPlay, a community dedicated to game preservation, has organized a large-scale boycott dubbed #PSBlackout, urging PlayStation users worldwide to turn off their consoles for an entire week, from August 23 to August 30. The X post has amassed over 1.8 million views and 7,500 shares, but it is uncertain how many users will participate. In addition to this digital protest, a Change.org petition with more than 350,000 signatures is asking for Sony to reconsider its decision to end physical game production.

Sony has been winding down its physical media production over the years (for example, physical boxes with a download code), so it was just really a matter of time before the PlayStation ecosystem adapted to the changes. Unfortunately, the die is cast, and there are rumors that Sony has already started repurposing its factories for other endeavors. There is little to no hope that Sony will reverse its decision to discontinue physical game discs.

A retro shop owner based in Waukesha, Wisconsin, located some 15 miles west of Milwaukee, discovered that he was holding on to a rare stash of NES carts in his storage room. According to Nintendo Wire, these cartridges were never-before-seen versions of Duck Hunt and Super Mario Bros., which were some of the most popular games on the Nintendo Entertainment System. What’s more important is that these haven’t been opened, and the original owner said that these supposedly came directly from Nintendo of America. Their condition is so pristine that PSA (Professional Sports Authenticator) gave them extremely high grades of no less than 9.6, with five units getting the coveted perfect 10.

Kevin Braun, the owner of the retro shop OneStopWonders, said that a person sold him the cartridges years ago and that they’ve just been sitting untouched in his storage unit. The man said that his grandfather owned a business that recovered precious metals from circuit boards, and that this box was supposedly sold to him for salvaging. It’s unknown how it ended up in storage instead of recycling, but Braun bought it from the seller, thinking he could resell it in his shop for around $10 to $15 each.

Thankfully, he forgot about these cartridges until his friend and EIC of Nintendo Wire, Jason Ganos, got a chance to look at them. When he saw the carts for the first time, Ganos knew that he was looking at something special but didn’t realize how exceptional they were until he shared the find on a high-end gaming Facebook group. Two different people working as directors at different grading companies then reached out to him, telling him that there was something strange about these cartridges. They then asked for more photos of one cartridge and the manual and even told him to disassemble one unit for a deeper inspection.

This is where he discovered that these cartridges were some of the last produced units made during the 40th week of 1993. The manuals weren’t seen before, either, with the back page saying, “maintenance or service,” whereas previous known versions said, “maintenance or repair.” Because of these finds, he proceeded to take a flight to PSA in California early the next morning, where the grading company confirmed its authenticity.

It seems that the cartridges in the box were made as replacements for warranty repairs or refurbished consoles, or as part of a bundle that never saw release. We would never know which is true, though, unless Nintendo of America confirms why they were made. If you’re an avid collector or simply want to get your hands on an original Nintendo game that hasn’t been released, three carts will be auctioned off at Goldin Auctions starting August 12.

It’s unclear how much these carts will go for, but it’s estimated that they’d cost at least four digits, with the perfect 10s possibly hitting five digits. This is possible, given that an ultra-rare NES Gold Nintendo World Championships cartridge auction sat at $77,000 and probably sold for a much higher price. So, if you want to get your hands on this, you’d better have a war chest of at least $100,000 to guarantee that you can get one — just don’t blow on it if you insert it in your NES console and it doesn’t work for the first time.

A Nintendo DS game that was classified as ‘lost media’ for nearly two decades is currently within tantalizing reach of video gaming fans and archivists. All the fans need is about $9,100, and no rival bidders on an eBay auction for an ultra-rare, perhaps one-of-a-kind, development cartridge thought to contain the PokePark Fishing Contest DS minigame.

Japanese game archaeology enthusiast Yoshino @ Federation (renpou.com) shared details of the eBay auction and its significance to their tens of thousands of social media followers.

So, what’s the deal with PokePark Fishing Contest DS, and why is it ultra-rare or even classified as ‘lost media?’ This fishing mini-game was lost for several reasons. Firstly, it was a download-only title. Secondly, its distribution was limited to those attending a short-lived Pokémon theme park venue in Japan (PokePark 2005). It also eluded archivists because it would be removed from a DS handheld when it was powered off, or after a 12-hour limit, whichever triggered first.

The eBay listing shows a large development and testing cartridge, front and back. There’s also an image showing the cartridge working. However, the on-DS-screen proof of viability is limited to “a Japanese-language screen indicating a high-score ranking communication program.”

The Germany-located seller, catbearpaws, says the cart was acquired as part of a private lot, and is selling the hardware as-is, with no promises regarding functionality, compatibility, or provenance. Catbearpaws has a 100% selling record and is asking for bids starting at €7,999 ($9,100), with less than three days left to run. They also may accept offers via the eBay Make Offer button/process.

Our machine-translated version of the eBay listing screen content appears to confirm that this is indeed a dev cart that was used for hosting “PokePark Fishing Contest DS” assets of some kind. Whether a playable version of the game can be downloaded, transmitted, or extracted from this hardware remains to be seen. As mentioned, the seller isn’t guaranteeing anything about this expensive but potentially important retro gaming artifact.

Amazon, Google, Meta, and Microsoft have spent more than a trillion dollars on AI infrastructure, including data centers, the chips inside them, and the power needed to run the facilities, since 2023. The Financial Times said that these four big companies have already hit $1.1 trillion in capital expenditure based on their latest earnings reports, and that an additional $745 billion is expected to be added to this figure just this year.

“There is basically no end in sight for the growth in capex,” RBC Capital analyst Rishi Jaluria told the publication. “Investors need these companies to toe the tight line between investing in AI and not compromising the things that have made them successful.” This massive investment has upended several other industries — namely electricity prices and memory and storage chips. The massive power demand that data centers have put on the power grid has forced many U.S. utility companies to spend billions of dollars to upgrade their respective infrastructure, which they then passed on to all consumers, not just the big ones that forced the upgrade.

This, alongside other environmental issues, has caused many Americans to push back against data center projects near their communities. The White House instituted the “ratepayer protection pledge” and made AI hyperscalers, utility operators, data center companies, and individual states promise that they will protect the average consumer from electricity cost increases. But so far, no state has taken a step to codify this pledge into law. Oregon actually enacted the POWER Act, which resulted in a 30% increase in the power bill of users that consumed more than 20MW while slashing the bills of residents by 1.3%, but the state did this in 2025, way before President Donald Trump called the tech giants into the White House and told them to “pay their own way.”

The mountains of cash that these tech giants are pouring into AI are also affecting the memory and storage chip industry. Since these AI hyperscalers have a lot of liquidity from investors, they are willing to pay top dollar for the HBM they need to run their data centers. Because of this, it made sense for Micron, Samsung, and SK hynix to prioritize them over DRAM, especially as they can charge a premium for these chips and there are customers who are willing to pay at those prices. This resulted in a shortage of consumer memory that started in 2025 — while this initially affected PC builders and enthusiasts, it has started to affect other industries that require memory as well, including cars and smartphones. Even Apple, which historically had huge sway over its suppliers, was forced to increase prices because of the shortages.

Aside from skewing other industries, the massive CAPEX the big four are going into is alarming some experts, warning that the promises and contracts they’re making are leading to “hidden debt” not listed in their balance sheets. The amount, worth around $1.65 trillion, is annotated in their quarterly financial statements as future obligations that will only come into play as the related asset or service comes online. The current value is 122% of the actual debt reflected on their balance sheets, which could give investors the wrong impression that they have fewer obligations than they actually have.

While the amount of money that the big four are spending on AI might seem dizzyingly high, we must note that these companies are raking in massive amounts of cash quarterly themselves. Microsoft’s latest quarterly revenue is $90 billion, while Meta made $60 billion in the same period. Alphabet (Google) announced revenue of nearly $120 billion, while Amazon made $200 billion. That is a total of nearly $470 billion for these companies in just the last quarter.

Still, that does not mean that they can just keep on spending on AI. For example, even though Google’s cloud business had a revenue of $11 billion last year, its price dropped after it announced that it spent more than it made last quarter — the first time this happened in the 20 years since it went public. Meta is also planning to rent out its AI compute, apparently following in the footsteps of Amazon, Google, and Microsoft, which have growing cloud businesses. However, this announcement caused a drop in its stock price. “They are a bit all over the place,” SLC Management managing director Dec Mullarkey told FT. “For investors it’s no longer growth at any cost; they want to see the spending flowing through to results, like at the Big Three.”

We're celebrating the 30th anniversary of Tom's Hardware. Since the beginning of Tom’s Hardware in 1996, we’ve been covering CPUs. Over the course of the past 30 years, we’ve maintained a comprehensive list of the best CPUs for gaming by reviewing each new release, and we’ve compiled thousands of data points spanning years to compile our CPU benchmark hierarchy. From the Pentium II and the introduction of Dual Data Rate memory to dual 3D V-Cache CPUs, Tom’s Hardware has been there for it all.

It’s time to look back, not just on Tom’s Hardware’s role in the world of CPUs over the past 30 years, but on the broader CPU market. Earth-shattering releases at a given time turned out to be footnotes in hindsight, and bubbling competition that seemed like no real threat turned into seismic shifts in the AMD vs. Intel battle. Hopefully, along the way, we’ll see some reflections of what’s going on in the world of CPUs today.

This is a celebration of 30 years of CPU coverage here at Tom’s Hardware, a history lesson about how the AMD and Intel of yesteryear arrived at the positions they’re in today, and a retrospective of the CPUs that stood the test of time against the refreshes that faded into obscurity just as soon as they were released. We hope you enjoy it.

Ruffling feathers from day one (1996 - 1998)

Ruffling feathers from day one (1996 - 1998)

Like much of the early internet, the true beginnings of Tom’s Hardware (or, rather, Tom’s Hardware Guide) is difficult to pin down, but the earliest archived article concerns the SoftMenu BIOS, which allowed you to change CPU settings through software rather than physical jumper cables; it should go without saying that this article was from July 1, 1996. There were articles before this one, with the original domain of sysdoc.pair.com going online in February 1996.

Tom’s Hardware gained a lot of traction a year later with a CPU review: a look at the Intel Pentium II ‘Klamath’ processor.

Tom’s Hardware’s founder, Thomas Pabst, had discussed CPUs previously, like in a dense CPU guide published the same year, but the Intel Pentium II review marked a turning point. It was published March 1, 1997, more than two months before Intel launched the Pentium II 80522 (or Klamath). It was not positive: “...since I wouldn't eat [Mad Cow Disease] infected beef, I wouldn't be interested in risking an infection of my computer with this CPU either,” wrote Pabst.

The CPU wasn’t officially available, but Pabst was able to test the chip with a pre-release unit shared by two German magazines: C'T Magazin fur Computertechnik and PC Professionell. Following the publication of all three reviews, Intel targeted the two German magazines, threatening to withhold advertising dollars and take legal action against them. Pabst publicized this fiasco and was contacted by The New York Times, which also covered the story. Intel backed down. Pabst later wrote that “...this 'David against Goliath'-incident made Tom's Hardware Guide very famous.”

In the following months, Pabst focused on CPUs quite a bit, breaking from the performance-tuning guides and general enthusiast information the website had previously published. The situation with Intel made Pabst a “secret star,” so much so that AMD not only offered Pabst a free review unit of the upcoming K6, but also apparently offered to cover legal fees should Intel pursue the situation further.

Although the unofficial review of the Pentium II predates it, the first review that looks most like the technical reviews that have been published on Tom’s Hardware for decades came in April 1997 with a review of the AMD K6, a CPU that established AMD as a true competitor to Intel, claiming Pentium II-like speeds for less money.

The performance wasn’t quite on the level of a Pentium II, most notably because the K6 originally arrived at 233 MHz, when 266 MHz was promised. But it was competitive, particularly when compared to the Pentium II 233, and much cheaper. Pabst concluded the review, “All in all I'm sure that this CPU will be very successful… Whoever is contemplating the purchase of an Intel Pentium or Pentium MMX CPU can forget about this now. The AMD K6 is faster and cheaper.”

Later that same month, Pabst published a proper review of the Pentium II, now using finalized silicon. In DOS games and the 32-bit Windows NT, Pentium IIs showed a commanding lead over the K6, though the battle on Windows 95 was closer. “The world is back to normal. Intel’s managers can sleep quietly again. The Pentium II shows that Intel is still the leader in the CPU market,” the review concluded.

A review of the Cyrix/IBM 6x86MX went live in 1997, as well, showing competitive performance with the K6, but much of the rest of the year was focused elsewhere after the Pentium II/K6 showdown. Looking back, it’s interesting to note the dynamic at play between AMD and Intel, with Pabst using a running gag of referring to Intel as the “Empire,” and competitors like AMD and Cynix as “Rebels.” Although Intel backed away from further action on Pentium II, it wouldn’t be the last time Pabst and Intel butted heads.

The Pentium III incident (1999 - 2001)

The Pentium III incident (1999 - 2001)

The competitive performance of K6 brought AMD into focus as the rival to Intel, which Pabst often described as “almost-monopolistic” at the time. However, AMD really put itself on the map with the release of K7, or as it’s better known, Athlon, in June 1999. In our review, we described it as “a milestone in the whole processor scene,” due in part to AMD’s unique three-way instruction decoder, which allows instructions of variable complexity through all three lanes. Intel’s P6 architecture in Pentium III also had a three-way instruction decoder, but they were segmented based on the complexity of the instruction.

We’re still firmly in the single-core era of CPUs here, so an architectural divergence like this, even before testing, represented a goldmine of speed gains. Rather than releasing several variants of silicon sliced up in different ways, as we see with modern CPUs, Intel and AMD refined their chips and released new versions with faster clock speeds. AMD released the Athlon 600 as the fastest chip in the range at 600 MHz first, but less than two months later, it introduced the Athlon 650, and two months after that, the Athlon 700.

Intel was caught off guard and quickly introduced the Pentium III 600 to counter AMD. The original Pentium III range, codenamed Katmai, was largely a refinement of Pentium II ‘Deschutes’ chips; both were built using a 250nm node, in fact. In our original Athlon review, we noted instability with the Pentium III 600, suggesting the architecture couldn’t handle such high clock speeds.

The original ‘Katmai’ range of Pentium IIIs was short-lived, and later in 1999, Intel introduced a new revision called Coppermine. Coppermine introduced an on-chip L2 cache for Intel, and it was built on a 180nm node, allowing Intel to go from 9.5 million transistors on Katmai to 28 million on Coppermine, as well as push clock speeds up to 733 MHz with the initial range, squeezing out a minor increase over the Athlon 700. Less than two months later, AMD introduced Orion, or Athlon Model 2, which also used a 180nm node and clocked up to 750 MHz. This back and forth of minor clock speed improvements is going to stick with us for at least another half of a decade, so strap in.

The goal, of course, was the first 1 GHz CPU, a milestone that AMD claimed for itself in March 2000 with the introduction of the Athlon 1000. Intel had shown a 1 GHz Pentium III, but AMD released a 1 GHz Athlon first. Intel followed shortly after with its first CPU to hit the gigahertz milestone. Intel didn’t want to place second again, so it went to work on the Pentium III 1.13 GHz, which it introduced in July.

Pentium II made Tom’s Hardware a name in the PC industry, but the Pentium III 1.13 GHz gave it a name among enthusiasts. Our review found that the processor wasn’t stable at 1.13 GHz, and less than a month after introducing the chip, Intel recalled it. The Pentium 1.13 GHz would eventually come back in 2001, but at the pace of CPU innovation at the time, even a six-month delay was detrimental.

In June 2000, AMD introduced a refinement of Athlon, codenamed Thunderbird, and days before Intel’s recall, introduced the Athlon 1100. AMD remained uncontested throughout the rest of the year, pushing Thunderbird up to 1.2 GHz. Intel was closing the curtain on Pentium III and trying to move attention away from Athlon toward its upcoming Pentium 4 range.

Going for gigahertz (2001 - 2004)

Going for gigahertz (2001 - 2004)

Intel was struggling to keep pace with Athlon, but work was going on behind the scenes on the new NetBurst microarchitecture, which was set to become the successor to P6. It was introduced to the world with the Willamette core inside the first Pentium 4. Like most major microarchitecture shifts we’ve seen from Intel and AMD, NetBurst wasn’t an immediate success. However, Pabst noted in our review: “I am certain that Intel will deliver very fast Pentium 4 processors very soon. Intel has finally won back the ability to make AMD's life a lot harder.”

Intel pushed P6 down to a 130nm node with the release of Tualatin Pentium III chips, but the focus was on Pentium 4 and optimizing NetBurst. In March, AMD introduced the Athlon 1333, but Team Red was losing steam. Intel had already released a Pentium 4 1.5 GHz, and it introduced the Pentium 4 1.7 GHz (along with a price cut to the range) in April 2001. With a new microarchitecture seemingly bursting with potential, it was only a matter of time before Intel made its way back to the top.

That came in August, when Intel planted its flag on the 2 GHz milestone with Pentium 4, and beat out AMD’s fastest Athlon chip. AMD didn’t like that. Later in the year, in October, AMD introduced its Athlon XP range, and with it came a sneaky switch in marketing strategy. Rather than include the clock speed as part of the processor name (i.e., Athlon 1333), AMD started using model names. No, the Athlon XP 1500+ wasn’t clocked at 1.5 GHz; it was clocked at 1.3 GHz. This nomenclature climbed all the way to the top, with the Athlon XP 2100+, which was not 2.1 GHz, but rather 1.7 GHz.

At the time, AMD described this shift as an alignment with what it was able to deliver with Athlon. During this era, we start to see more significant architecture divergences between Intel and AMD, so much so that like-for-like clocks could result in vastly different performance. That’s what we found in our Athlon XP review, in fact, with the Athlon XP 1800+ (clocked at 1,533 MHz) contesting the Pentium 4 2 GHz. Still, it’s not hard to see what AMD was trying to do. In January 2002, Intel introduced its Northwood core for Pentium 4, which could clock up to 2.2 GHz. AMD wasn’t able to break the 2 GHz barrier yet, but it used product names to suggest it had.

Names weren’t enough. By the middle of 2002, Northwood had picked up steam and could clock as high as 2.8 GHz; even the 2.4 GHz Pentium 4 was able to beat AMD’s fastest Athlon XP 2100+ across our benchmarks. AMD was working on the Thoroughbred revision of Athlon XP, including a node shrink down to 130nm to match Intel’s new Northwood core, which it trickled out through 2002. By the end of the year, AMD had shown the Athlon XP 2800+ as a rival to the Pentium 4 2.8 GHz.

Despite lagging in clocks, AMD had become quite popular during this time due to the competitive performance of Athlon XP and (most importantly) a lower price point than the expensive Pentium 4s. Still, there was a stalemate in technology between Intel and AMD, and Intel would break it in November 2002 with the Pentium 4 3.06 GHz.

It was the first consumer CPU to clock to 3 GHz out of the box, adding another notch to Intel’s belt, but it was also the first CPU to bring Intel’s long-standing simultaneous multithreading implementation, called Hyper-Threading, to market. With higher clocks and two threads to play with, the Pentium 4 3.06 GHz cemented Intel at the top of the performance charts, beating out AMD’s fastest Athlon XP and even a 3.6 GHz Pentium 4 (no Hyper-Threading) in some benchmarks. Tom’s Hardware actually benchmarked the Pentium 4 3.6 GHz nearly a year before it was available, and had data in time to compare to the Pentium 4 3.06 GHz with Hyper-Threading.

More cores, more fun (2004 - 2007)

More cores, more fun (2004 - 2007)

The clock speed battle from the late 90s and early 2000s was starting to fall apart. AMD had demonstrated that performance was more than peak clocks with Athlon XP, and Intel was pushing ahead with Hyper-Threading to get more work done simultaneously each clock cycle. The first half of 2003 was dull in the world of CPUs as Intel worked on its Prescott core and AMD mulled over “ClawHammer,” which would eventually become Athlon 64.

Athlon 64 would be the first to bring AMD’s x86-64 ISA extension (called AMD64) to the desktop market (it previously showed up in Opteron). It rolled out in September 2003, and just a week before release, Intel launched the Pentium 4 Extreme Edition, which was widely considered a panic switch in response to Athlon 64 while Prescott was still under wraps. Although Intel maintained the performance crown with P4 Extreme against the Athlon 64 FX-51, it did so at a much higher price.

Still, this late-stage battle as Intel and AMD moved toward a 90nm node was important. Intel started marketing expensive, high-performance processors directly to enthusiasts in a market that would eventually get the HEDT, or high-end desktop, name. Meanwhile, AMD designated some Athlon XP chips with the FX name, which signaled high-performance chips with unlocked multipliers.

Intel was first to get down to 90nm with its highly anticipated Prescott core, though it arrived with a whimper. It clocked slower, allowing the FX-51 to remain competitive and Northwood chips to remain at the top of the charts in our review. There, our reviewer Patrick Schmid wrote: “In our opinion, Intel today does not care about Prescott as a processor, but as a marketing instrument. It is fast enough, which is mainly what counts, and since the 90 nm production process yields cheap processors in vast quantities, the Santa Clara-based company gains new flexibility.”

AMD made it down to 90nm later in the year with the FX-55. The FX-55 allowed AMD to close the gap with higher-clocked Pentium 4s, as we found in our review. However, it was becoming clear that the chase for higher clocks wouldn’t be enough. In our review, Schmid wrote in 2004: “Today, the performance gap between the fastest and the slowest processors in our benchmark charts is rather small.”

Intel fired back at the beginning of 2005 with Prescott 2M, a minor revision to the Prescott core with 64-bit ISA extensions, and released the Pentium 4 Extreme Edition 3.73. The tide shift came in the summer of 2005 when AMD launched the Athlon 64 X2, built on a 90nm node, and featuring two cores on the same package.

Intel had released its double-core Pentium D just weeks earlier, which was also a dual-core chip, but the design forced Intel to compromise clock speeds — an important spec given how few applications could actually leverage a dual-core chip in consumer software. AMD ultimately won the battle with the Athlon 64 X2, largely due to the fact that it could keep pace with single-core Athlons in most benchmarks, as you can see in our early preview of the chip.

AMD released more Athlon 64 X2 chips throughout 2005, while Intel rolled out various chips under different Pentium brands, including the Smithfield core on Pentium D. Intel built out the range into 2006, using another node shrink down to 65nm with the Presler core, which was the final revision under the Pentium brand. In January 2006, Tom’s Hardware first reported that Intel planned to drop the Pentium brand, a name that it had kept for over a decade.

In its place? The new Core microarchitecture, finally moving on from NetBurst, which had been plagued with thermal issues as clocks climbed. Built out of Intel’s work in mobile chips, the Core 2 Duo was Intel’s first proper dual-core processor — the “double-core” Pentium D was just two Pentium dies fused together. It was a tide shift.

As we found in our Core 2 Duo review, the base E6600 and E6700 often beat, or at least matched, AMD’s Athlon 64 FX-62, while the supercharged Core 2 Extreme X6800 established a new performance tier at the high-end. Further, it did so at reasonable power levels, finally taking the efficiency fight back to AMD.

Intel doubled down, literally, with the Core 2 Extreme QX6700 at the end of 2006. Although Intel had introduced a four-thread processor previously, the Core 2 Extreme QX6700 was the first CPU with four cores to hit the market. It took two dual-core dies from Core 2 Duo and put them together on a single package. AMD brute-forced a quad-core with the 4x4 platform and dual Athlon 64 FX-70 chips, but there was a major tradeoff in cost, thermals, and power demands.

The coast of Nehalem (2007 - 2010)

The coast of Nehalem (2007 - 2010)

For the first time in the early aughts, Intel was firmly in the driver’s seat for enthusiasts. AMD drummed up some interest with its dual-chip Athlon 64 systems, and it finally moved down to a 65nm node at the start of 2007. But Intel was on a tear, and it would continue its momentum for years to come.

That started by formalizing the success of the Core microarchitecture. Instead of squeezing everything out of a microarchitecture for several generations, as it had done with P6 and NetBurst, Intel transitioned to its well-known tick-tock cycle. First, there’s a node shrink on its existing architecture, then there’s a new microarchitecture on that node, and the cycle continues. Core was the tock at 65nm, and it would move down to Penryn revision at 45nm later in 2007.

AMD struggled to keep pace. After introducing its AM2 socket in 2006, it continued refining the Athlon 64 X2 lineup with a new 65nm node, but Intel was firmly in the lead, forcing AMD to slash prices and settle into the market as a budget-focused alternative to the shiny Core 2 Duos. AMD doubled down in this area with its K8 microarchitecture, releasing a series of efficient “BE” series chips throughout the back half of 2007, which we found were excellent for efficiency and price-to-performance in our review.

Team Red had its chips on K10, and specifically, the new Phenom brand that it made noise about throughout 2006 and 2007. The Phenom X4 series launched in November, featuring the first true quad-core design; that is, using a monolithic die as opposed to MCM like Intel’s Core 2 Quad. Unlike Intel’s Core 2 Extreme, which was reserved for only the most entrenched enthusiasts, AMD targeted midrange builders.

In our Phenom 9700 review, we found that Intel still maintained the performance crown, but AMD offered a cheaper quad-core and offered identical price-to-performance at release. Further, AMD offered support for the chips on both the AM2 socket and the new AM2+ socket, starting a trend of socket longevity that we can still see in action today. With cheaper quad-core CPUs and less upgrade cost, AMD focused less on battling Intel at the high-end and more on delivering in the midrange.

Intel continued to release more Core 2 Duo and Core 2 Quad models throughout 2008, but behind the scenes, it was working on its next major architectural shift: Nehalem. AMD built out its Phenom line, meanwhile, introducing a tri-core variant, as well as several “Black Edition” models that featured peak clocks and unlocked multipliers for enthusiasts, likely in a bid to grab some attention from Intel’s Extreme lineup.

Nealem came onto the scene in late 2008 in the form of Bloomfield chips. They required an entirely new platform and DDR3 memory, but also promised entirely new performance benefits. Intel managed to create a true quad-core chip with Bloomfield, and one that enthusiasts could actually afford, with the range going down as low as $280. Further, it reintroduced Hyper-Threading after ditching the technology during the early dual-core days, giving enthusiasts eight threads to play with.

The spread between Intel and AMD grew wider. In our review of the Core i7-965 Extreme, we found it was 64% faster than AMD’s fastest chip at the time. Despite offering compelling products at competitive prices, AMD was falling further behind. Intel was far ahead; it had a die shrink ahead, and the legendary Sandy Bridge microarchitecture was waiting in the wings to pick up the tick-tock cycle once again.

AMD bit back in early 2009 with Phenom II (along with Athlon II), finally moving down to 45nm. It brought Team Red back up in the rankings, but Bloomfield still held onto top-end performance. In our original Phemon II review, we found that Intel was about 22% ahead of AMD at the high-end, but AMD offered compelling performance given the platform costs. Sounds familiar.

With tight integration of design and manufacturing under one roof, Intel was moving faster than AMD on process improvements, allowing it to keep a consistent lead in performance, particularly at the high-end. Intel had its Lynnfield chips at 45nm, as well as Clarkdale chips at 32nm, but the 32nm successor to Bloomfield came in early 2010, known as Gulftown. And with Gulftown, Intel could claim a multi-core milestone on a monolithic die for the first time with the six-core Core i7-980X.

At $1,000, the Core i7-980X still only appealed to a small number of enthusiasts. AMD helped fill the gap later in the year with the Phenom X6 launch, introducing six-core models of its own. AMD couldn’t match the 980X at the high-end, but Phenom represented an affordable entry-point to six-core chips if you ran heavily-threaded workloads, as we noted in our review. Still, Phenom X6 was AMD trying to keep pace with Intel. Behind the scenes, AMD was working on a new microarchitecture called Bulldozer, which was built from the ground up for a new generation of chips and finally allowed AMD to move down to 32nm.

Bulldozer bulldozes world records, thermals (2010 - 2013)

Bulldozer bulldozes world records, thermals (2010 - 2013)

It’s easy to pick on Bulldozer in hindsight, but leading up to release, the anticipation was palpable. K8 was a smash success, and K10 built on that success, but Bulldozer was built from the ground up, presumably for the position AMD had found itself in the market. Nearly a year before Bulldozer showed up on the market, however, Intel introduced an architecture that still resonates among enthusiasts today — Sandy Bridge.

Intel unified its product stack with Sandy Bridge and set much of the foundation for the company’s releases through Raptor Lake Refresh. Instead of two broad ranges, Intel placed most of the Sandy Bridge lineup on a single socket. It also brought integrated graphics to all the chips in the lineup, at least in the initial range (some later releases cut the iGPU), as well as unlocked the multiplier on some non-Extreme SKUs to compete with AMD’s unlocked Black Edition chips.

It was a smash success. Reviewing four Sandy Bridge chips, our reviewer Chris Angelini wrote: “Existing Lynnfield- and Clarkdale-based processors already offer strong performance compared to AMD’s lineup. Significant gains, clock-for-clock, compound in the face of notable frequency increases across the board (thanks to a mature 32 nm process), giving Sandy Bridge an even more commanding position.”

Raw performance improvements are one thing, but Sandy Bridge was attractive for several other reasons, as well. Overclocking still represented a solid performance boost in this era, and Intel was offering overclocking capabilities at mainstream price points alongside chart-topping performance out of the box. They also introduced Quick Sync to accelerate video encode/decode, and although we have video encode/decode acceleration in modern GPUs, Quick Sync still serves as a fundamental feature for video editing and media servers.

AMD’s response was Bulldozer, which was rumored ahead of release to outperform Intel’s Core i7-950 by upwards of 50%, as well as introduce a true eight-core chip to the consumer market for the first time. If that wasn’t enough, prior to release, the flagship FX-8150 set a world record for clock speed, peaking at 8.429 GHz. AMD would be the first to release a consumer CPU with eight cores, but just about every other aspect of Bulldozer was problematic.

Achieving eight cores in a single package came with significant trade-offs. Up to this point, AMD hadn’t used any form of simultaneous multithreading, but it implemented a version of SMT in Bulldozer. Unlike Intel’s traditional SMT implementation, Bulldozer used two integer units on a core, but shared floating point resources. The major trade-off was how small the integer execution clusters were in order to save space. AMD designed an architecture for a world of heavily-threaded software that just didn’t exist at the time, and it traded very important single-core speeds to achieve that design.

The flagship FX-8150 was marketed as an eight-core chip, with the eight-core count coming from AMD’s odd SMT implementation. Although there were two integer execution units per “module,” as AMD calls them, the floating point unit was shared. This discrepancy was actually the focal point of a 2015 lawsuit, which AMD settled in 2019 to the tune of over $12 million.

It was a flop. Angelini sums up the issue nicely in his October 2011 review of the FX-8150: “[Intel doesn’t] have to do anything at all. Its nearly year-old 95 W parts fend for themselves without even a price adjustment.” Intel had new chips of its own, as well. Just six months later, it introduced Ivy Bridge, taking the solid foundation of Sandy Bridge and moving it down to a 22nm node.

Ivy Bridge wasn’t a big hit on desktop, but it didn’t need to be, given the advantage Intel had already established with Sandy Bridge. Improvements were in the single digits, as we noted in our Core i7-3770K review, but Ivy Bridge brought improvements to integrated graphics to fight against AMD’s burgeoning lineup of APUs and thermal improvements targeting small form factor devices — especially laptops in a new category of “ultrabooks” that Intel was targeting.

12 months after the FX-8150 was introduced, AMD released a revision of the Bulldozer architecture named Piledriver. It promised better IPC and higher clock speeds, which was compelling, as AMD’s FX-4170 released earlier in the year as the first CPU to hit 4 GHz out of the box. Piledriver had a test run earlier in the year through AMD’s Trinity APUs, as well, showing around a 15% improvement compared to Bulldozer.

The flagship Piledriver, the FX-8350, was indeed better than its Bulldozer predecessor, but it was clear the underlying architecture had issues that wouldn’t allow AMD to scale up. AMD’s flagship was only competitive with Intel’s Core i5 options, and power use, although tamed in Piledriver, still meant the chip ran hot. It was immediately forced into a price cut upon release. After two failures to launch flagships, Intel effectively owned the high-end, which it continued to dominate with CPUs like the Core i7-3970X.

Around six months after Piledriver chips shipped, AMD released another two chips, both running at an insane 220W TDP and shipping with their own liquid cooling system. The highest-end offering, the FX-9590, was the first CPU to hit 5 GHz out of the box. AMD had learned the hard way what it had preached back in the Athlon XP days — clock speed isn’t everything.

The dawn of 14nm (2014 - 2016)

The dawn of 14nm (2014 - 2016)

With a 22nm product shipped, Intel went back to a tock and came out the other side with Haswell. Today, Haswell is heralded as a legendary architecture; we’ve all seen forum comments about gaming with a Core i7-4770K more than a decade after it was released. At the time, however, it established a narrative that would follow Intel for the next several years. That narrative being that Intel ships a new generation of quad-cores, each year, with minor IPC improvements and not much more. That’s certainly the impression Angelini came away with after reviewing the Core i7-4770K.

Intel didn’t have to move the needle beyond that point. Although AMD had shipped Bulldozer and Piledriver, a lot of turmoil was going on behind the scenes. Two further revisions of Bulldozer, Steamroller, and Excavator were planned, but AMD largely canceled the two revisions outside of a few low-end products. During this time, AMD underwent a series of sweeping layoffs and executive changes, cutting thousands of employees. Looking back at the time through a modern lens, some long-time AMD employees say that the company would’ve faced bankruptcy had it not been for semi-custom partnerships with Microsoft and Sony for their game consoles.

From the release of Piledriver in late 2012 through 2017, AMD didn’t release a ton of new CPUs. It released some revisions of Piledriver chips like the FX-8370, but we didn’t see any new microarchitecture. And planned node shrinks with Steamroller and Excavator were canned, with only a handful of desktop CPUs surviving, which were repurposed as low-end Athlon X4 CPUs years later. Intel had won.

It didn’t immediately rest on its laurels, however. Hearing the criticism of Haswell for desktop enthusiasts, Intel introduced the Core i7-4790K alongside other ‘Devil’s Canyon’ chips in mid-2014 as it worked on another tick behind the scenes down to 14nm. The result, which arrived almost a year to the day after Devil’s Canyon, was Broadwell. The Broadwell-H range — not Broadwell-E, which shows up later — isn’t very big and didn’t have much for enthusiasts. But Broadwell got Intel down to 14nm, and it would stay there until the release of Alder Lake CPUs in 2021.

We didn’t know that at the time, though. Broadwell laid the 14nm foundation for Skylake, which came hot on the heels of Broadwell-H after that architecture experienced a series of delays. Intel’s first true eight-core chip, the Core i7-5960X from the Haswell-E range, still gave the HEDT market what they were looking for, but Skylake was pushing ahead in the mainstream. In early performance testing, we said Skylake was the first architecture “to really get enthusiasts excited since Sandy Bridge.”

Intel didn’t need to rush at the time, so it didn’t. There wasn’t an Athlon 64 breathing down Team Blue’s neck. A year later, in 2016, Intel launched Broadwell-E for HEDT, marking the first-ever 10-core desktop CPU with the Core i7-6950X. It wasn’t a massive leap forward over Haswell-E, but Intel was competing with itself. “Intel’s clearly the prettiest girl in the room, is well aware of this fact and, based on Broadwell-E's pricing, doesn't need to beat the ‘value’ of last generation's -Es by much,” our reviewer Igor Wallossek wrote in his Broadwell-E review.

Although Intel was a clear market leader, it was slowing down significantly. Earlier in 2016, it quietly revised its tick-tock cycle, moving to a tick-tock-tock cadence where we’d see a new process followed by a new microarchitecture followed by an optimization of that architecture. Intel wasn’t juiced up with Moore’s Law like it was in the early aughts, but it competed in a category of one. What were you going to do? Buy AMD?

Feeling Zen (2017 - 2020)

Feeling Zen (2017 - 2020)

Shortly after the ball dropped into 2017, Intel released its Kaby Lake range of CPUs, now sporting the “14nm+” process and serving as the first optimization pass in Intel’s new release cadence. It was fine. The range came with a clock speed bump over Skylake, but otherwise, Intel released the same architecture sporting nearly identical specs, from core counts to cache sizes.

Behind the scenes, trouble was brewing. Six months before Kaby Lake made its way to market, AMD detailed its first entirely new microarchitecture since Bulldozer, named Zen. In addition to promising a 40% improvement in IPC over Excavator, the Zen platform would come with support for DDR4 and finally move AMD down to a 14nm node. For the architecture itself, AMD implemented SMT, completely redesigned its cache hierarchy, and added a micro-op cache to aid an updated branch predictor.

Two months after Kaby Lake rolled out, AMD launched the Ryzen 7 1800X. The revolution didn’t happen in a day. In our Ryzen 7 1800X review, reviewer Paul Alcorn (now Tom’s Hardware editor-in-chief) wrote: “AMD's Ryzen 7 launch represents more than just a new CPU family. For most of our readers, it signals the return of competition to the enthusiast-oriented processor market. And considering the flagship 1800X’s potent cost advantage compared to Intel's Core i7-6900K… Ryzen 7 does deliver. It's just not as universally superior as the company wanted everyone to believe.”

AMD still had quite the year ahead. A month later, the Ryzen 5 1600X launched with performance that could rival Broadwell-E, just for a much cheaper price. And by Summer, the Ryzen 3 1300X proved you didn’t need an expensive CPU and motherboard to get into overclocking. AMD capped its Ryzen rollout with Threadripper, scaling up the Zen microarchitecture to massive core arrays and finally bringing something to the HEDT market — a market that Intel had almost wholly owned since the Pentium 4 days.

Still, Zen had shortcomings, particularly in games, where just about any quad-core from Intel still ruled the roost. AMD was competitive, but Intel was still firmly in the driver’s seat. It barely reacted to the Ryzen onslaught over the summer, rolling out its high-end Skylake-X and Kaby Lake-X HEDT offerings throughout the back half of 2017. Even then, however, problems started emerging.

Kaby Lake-X was effectively a rerelease of Kaby Lake with a bit of extra headroom, but restricted to the expensive X299 platform. It was discontinued less than a year after release. Skylake-X was Intel’s true next-gen HEDT offering, signaled by the first use of “Core i9” in front of its flagship SKU. It performed like an Extreme Edition, and it was priced like one too, despite an issue in thermal dissipation that we uncovered in our Core i9-7900X review. Meanwhile, AMD was rapid-firing firmware and chipset updates for its small Ryzen range, and fixing several issues that came up in reviews in the process.

Less than a year after Kaby Lake launched, Intel released Coffee Lake, which was yet another Skylake revision built on 14nm, but this time with extra cores in tow. As you can read in our Core i7-8700K review, Coffee Lake did what Intel wanted it to do, shoring up the fight in heavily-threaded productivity applications against AMD while maintaining leadership in games. Still, AMD was making headway. By the end of 2017, estimates suggest AMD took back anywhere from 2% to 12% market share from Intel, with the higher end of the spectrum coming mainly from the DIY PC market. That’s no small feat for a company that was dead in the water with CPUs 12 months earlier.

Back on more even footing, the next goal post was a node shrink. Intel was gunning for 10nm, which is a milestone it failed to meet with both Kaby Lake and Coffee Lake. AMD, as a fabless designer, was at the mercy of its then-partner GlobalFoundries for the next node shrink. AMD struck first with Ryzen 2000 in early 2018, built on GlobalFoundries 12LP node, which was a revision of the 14LP (14nm) node used in the original Zen. Fittingly, AMD called it Zen+.

Debuting the architecture was the Ryzen 7 2700X, which was an iterative update. However, it helped reacquaint the market with the progress AMD had made. Zen+ came with higher frequencies and reduced memory latency, and all of the software adjustments AMD had made after the original Zen launch. And the range seemed specifically designed to undermine Intel, offering overclocking support across the full stack (and with B-series chipsets), and bundling a surprisingly decent cooler in the box.

Intel still held the edge in gaming, but the margins were narrowing, especially with a bit of overclocking thrown into the mix. Intel was feeling the heat, due in no small part to its continued issues moving down to 10nm. It responded in late 2018 with Coffee Lake Refresh, bringing the Core i9 branding into its main lineup for the first time with the Core i9-9900K and offering an eight-core, 16-thread chip. The strategy, it seems, was to push out AMD at the high-end, as Ryzen 7 was closing in on Core i7.

It worked. Intel had the fastest gaming processor on the market, and even the Core i7-9700K managed to push Intel’s lead in the Ryzen 7 battle higher. These marginal updates were buying time for AMD and Intel. Both companies clearly understood that whoever could go below 14nm first would have a massive advantage, and likely define an entirely new market dynamic.

AMD claimed that advantage for itself with the introduction of Zen 2 in mid-2019. Bolstered by TSMC’s 7nm node, AMD pushed out the Ryzen 9 3900X, moving beyond eight cores to AMD’s first 12-core consumer design. Intel held a slight edge in gaming through Coffee Lake Refresh, as you can read in our Ryzen 7 3800X review, but that delta was becoming less important as AMD took the lead in heavily-threaded workloads.

Later in the year, AMD rolled out the Ryzen 9 3950X, the first 16-core desktop processor ever. It was a bloodbath. Less than a year earlier, Intel had introduced its Skylake-X HEDT platform, including the Core i9-9980XE priced at $2,000. Now, at stock settings, the $750 Ryzen 9 3950X offered better multithreaded performance, along with competitive single-threaded and gaming performance. And you didn’t need to shell out for Intel’s expensive HEDT platform. And you could unlock PCIe 4.0, whereas Skylake-X (and even the following Cascade Lake-X) were locked to PCIe 3.0. You don’t spend top dollar on an HEDT platform for last-gen connectivity.

Intel was getting pushed into a corner, and it followed up less than six months later with Comet Lake to stave off AMD’s Ryzen onslaught. The flagship Core i9-10900K allowed Intel to maintain the lead in gaming, but now, AMD was in a clear lead in applications with the Ryzen 9 3950X.

Reviewing the Core i9-10900K, Alcorn wrote: “The Core i9-10900K is exactly what we would expect from an overclocked 10-core 14nm Skylake derivative: Exceptional performance in gaming and lightly-threaded workloads, competitive performance in multi-threaded work, and downright ugly power consumption and thermal output. And that's pretty much what you get with the Core i9-10900K – an overclocked 14nm processor right out of the box.”

AMD didn’t let up. It moved onto Zen 3 later in the year, launching its 16-core Ryzen 9 5950X alongside the main range in late 2020. And with its fourth Ryzen salvo launched, the battle was over. Opening our Ryzen 9 5950X review, Alcorn wrote, “With the Ryzen 5000 series, it's fair to say that AMD has finally, and fully, eclipsed Intel's performance dominance in desktop PCs.” It was a clean sweep, with AMD taking the lead in gaming, multithreaded, and single-threaded performance. Three years and four CPU generations later, AMD was back on top.

Forging a new path (2021 - 2024)

Forging a new path (2021 - 2024)

In the years leading up to 2021, it had become clear that a tick-tock, or even a tick-tock-tock, wasn’t possible any longer. Process shrinks were arriving later, and a pesky little pandemic threw the tight supply chain required for chip manufacturing into a frenzy. Both AMD and Intel knew they needed a different approach, but that would manifest in wildly different ways.

Intel was all-in on a hybrid architecture, using a mixture of microarchitectures on a single package to bolster core counts, similar to Arm-based designs. Intel talked a lot about Alder Lake leading into 2021, overshadowing its own launch of 11th-Gen Rocket Lake chips. The flagship Core i9-11900K was a massive disappointment, carrying all of the issues of the previous-gen Core i9-10900K while packing two fewer cores. Yes, Intel actually cut two cores from its flagship.

It seems Intel knew the issues with Rocket Lake. The chips launched with little to no fanfare, and as opposed to a gradual rollout like we see with most CPU generations, Intel blasted every model of Rocket Lake onto the market, knowing full well that Alder Lake chips would take their place eight months later. AMD, with renewed confidence, slowly built out the Zen 3 lineup with new APUs and variations of Ryzen 5000 as it worked on its next-gen Zen 4 architecture.

In late 2021, Intel swept Rocket Lake under the rug with the release of Alder Lake. Intel had finally moved on from 14nm with Intel 7 (10nm), and it was mostly successful. Intel reclaimed top placements in gaming, multithreaded, and single-threaded performance, and although the margins were thin, Alder Lake made it clear that Intel wouldn’t go quietly. “The Alder Lake processors mark a massive generational leap forward for Intel in nearly all facets, including gaming, performance in lightly- and heavily-threaded work, power consumption, overclocking, and platform connectivity options,” wrote Alcorn in our Core i9-12900K review.

AMD was working on something unique of its own, however. Zen 4 was in the oven, and it was clear there would be a competitive battle with Alder Lake. But before Zen 4 arrived, AMD introduced the Ryzen 7 5800X3D. It was the first processor with AMD’s 3D V-Cache packaging, and at the time, it looked like a slightly-tuned processor targeting gamers, with somewhere in the range of a 10% to 15% uplift in gaming performance specifically. In a surprising turn, the speculation actually undersold just how big of a deal the Ryzen 7 5800X3D would become.

Six months after the release of the Core i9-12900K, AMD was back on top of the gaming charts with the Ryzen 7 5800X3D, no less sporting a last-gen architecture and an SRAM stacking technique that limited boost clocks and locked the multiplier down. It outran the Core i9-12900K by nearly 10% in games while costing hundreds less, and it was nearly 30% faster than a stock Ryzen 7 5800X, as you can see in our Ryzen 7 5800X3D review.

Intel would come back with Raptor Lake in late 2022, but the Ryzen 7 5800X3D established a new category of true gaming CPUs that traded some application performance for peak frame rates. And that’s a category of chips that even today Intel hasn’t managed to crack.

AMD came first, however, launching Zen 4 in September 2022. The flagship Ryzen 9 7950X managed to leapfrog the Core i9-12900K, as you can see in our Ryzen 9 7950X review, but not by much, and the Ryzen 7 5800X3D remained at the top of the gaming charts. Immediately, speculation around 3D V-Cache chips for Zen 4 went into motion. Also tampering the Zen 4 release was an entirely new platform, which required costly DDR5 memory.

Intel capitalized with Raptor Lake mere weeks later. The flagship Core i9-13900K was back on top across tests, even managing to outclass the Ryzen 7 5800X3D in games. For the first time since the heyday of Athlon, we had a hotly competitive CPU market with AMD and Intel leapfrogging each other with each new release. Still, there was a niche that wasn’t being filled. 3D V-Cache disrupted the status quo for gaming processors, but it came with a significant trade-off to application performance. The stage was set for a CPU that could offer the best of both worlds.

AMD delivered that in early 2023 with the Ryzen 9 7950X3D and (to a much lesser degree) Ryzen 9 7900X3D. A couple months before, Intel cracked the 6 GHz barrier out of the box with the Core i9-13900KS, but AMD was offering something more compelling than peak clocks. The Ryzen 9 7950X3D managed to outclass Intel in multithreaded and single-threaded performance, all while offering a double-digit jump in gaming performance thanks to 3D V-Cache.

Raptor Lake saw a refresh later in 2023, and although the flagship was able to close the application performance gap in our Core i9-14900K review, AMD still held a firm grip on gaming performance, especially with the trimmed-down and relatively affordable Ryzen 7 7800X3D. AMD had taken the lead, but Intel, finally, executed its tick-tock-tock strategy and set its eyes on a radically new architecture in the form of Arrow Lake.

Reckoning with the real world (2024 - today)

Reckoning with the real world (2024 - today)

Under AMD’s thumb and clearly behind in pace, Intel needed to innovate. The result was Arrow Lake. Like Bulldozer, it’s easy to write Arrow Lake off in hindsight, especially given how recent it is. As you can read in our Core Ultra 9 285K review, Arrow Lake chips only marginally improved in application performance over their 14th-Gen counterparts, and they were actually slower across most games. But, architecturally, Arrow Lake is as big a swing as Bulldozer was.

For the first time, Intel outsourced manufacturing to TSMC, clearly behind the Taiwanese manufacturer for cutting-edge nodes. It disabled Hyper-Threading, killing off a staple of Intel CPUs for decades, and it doubled down on Intel’s hybrid architecture. Those bets didn’t pay off, but they were big bets for a company struggling to reckon with a reinvigorated AMD.

AMD followed up Zen 4, predictably, with Zen 5 in mid-2024, shortly before the Arrow Lake release. With Arrow Lakes' struggles, it’s easy to forget the problems Zen 5 had at launch, and the relatively small generational uplift it offers even today. AMD has continued to build out this lineup with X3D chips, and it finally delivered 3D V-Cache on both CCDs with the Ryzen 9 9950X3D2. But going back to our Ryzen 9 9950X review, Zen 5, at its core, isn’t the massive uplift we had become accustomed to in the early days of Zen.

Intel tried to give Arrow Lake a bit more life with a small refresh earlier this year in the form of the Core Ultra 7 270K Plus and Core Ultra 5 250K Plus, and those CPUs set the stage for the next era of CPUs. They put Intel into the position AMD found itself during the Bulldozer/Steamroller days, clearancing off silicon to maintain a competitive position in the market.

That’s where we are today, with our sights set on Zen 6 and Nova Lake. But there are some realities in the PC enthusiast space that we have to contend with today. DRAM pricing is out of control, and showing no signs of slowing down, and a sudden boost in demand for CPUs for agentic AI means consumer chips have taken a backseat. Zen 6 and Nova Lake were both expected by the end of the year; it’s looking more likely that they’ll slip into 2027.

History doesn’t repeat, but it often rhymes, and we can see traces of days past over the last 30 years start to creep into the dynamics today. Today, we see a defiant AMD and an Intel that seems ready to get scrappy in order to earn back market share. Will it pay off? We don’t know, but Tom’s Hardware will be here to cover whatever comes next in the world of CPUs, just as we’ve been for the past 30 years.

It has now been 30 years since our founder and namesake, Dr. Thomas Pabst, wrote the first articles that came to define Tom’s Hardware, focusing on providing unbiased, fact-based reporting backed by comprehensive testing, a mission that we strive to continue today. To celebrate our 30^th Anniversary, Tom’s Hardware is kicking off a series of articles that look back at the evolution of PC hardware and peripherals over the course of the last 30 years, with the first being a look at the evolution of the CPU. But before we dive into the history of CPUs and GPUs, let’s take a quick look back at the early history of Tom’s Hardware.

A then-practicing doctor and surgeon, Pabst began testing hardware in the early days of the desktop PC revolution, first publishing under the name of Tom’s Roadrunner Page in 1996, then rocketing the brand to fame after it evolved to become Tom’s Hardware Guide later that same year. In the early days, Pabst focused on testing motherboards and CPUs, but he also began testing graphics cards with the Nvidia Riva 128 being the first, followed by others like the 3Dfx Voodoo, among many, and he even penned a custom benchmark that was billed as the world’s first real-world 3D benchmark. Those foundational categories still live on today in our coverage.

Pabst’s biggest breakthrough came when he published an unsanctioned pre-release review of an Intel Pentium II CPU that he acquired from friends in the publishing business, who also published reviews. Naturally, Intel wasn’t fond of the resulting negative coverage, and the firm threatened to pull ads from two of the publications involved if the reviews weren’t removed. The ensuing spat garnered widespread coverage, with the conflict making it into the pages of the New York Times and other mainstream news outlets. Intel admitted to using its advertising contracts to threaten the sites and apologized, and the issue thrust the Germany-based Tom’s Hardware into the spotlight on the international stage right as CeBIT 1997 began, where Pabst met many of the industry contacts that helped move the site forward.

A few years later, Pabst discovered persistent bugs with the Intel Pentium III, some of which he exposed in Linux, which wasn’t commonly used for benchmarking at the time. Pabst refused to surrender his sample to Intel, saying it was his only proof of the issue. Due to the bugs Pabst discovered, Intel eventually pulled the processors from the market until a new chip stepping could be developed. Intel then excluded Pabst from coverage of the Pentium 4, which he viewed as another retaliation, sparking another very public conflict that cemented the brand's reputation for uncompromising independent journalism.

Tom’s Hardware Guide evolved over the intervening 30 years, spreading into new categories like networking and news coverage, eventually becoming known as Tom's Hardware — though it is still easy to spot our veteran readers because they still refer to the site as ‘THG.’ Pabst sold the site in 2007 to Best of Media Group and served as Chairman until 2008. Our sister site, Tom’s Guide, was born in 2007, and Tom’s Hardware has also branched out with multiple non-English licensees of the brand over the years, with Tom’s Hardware France and Tom’s Hardware Italy still operating to this day. Tom's Hardware was acquired by our current publisher, Future plc, in 2018.

PC building certainly looks a lot different today than it did when Pabst first began testing PC hardware. Back in those early days of the PC, things such as user-friendly BIOS tuning didn’t exist; enthusiasts simply adjusted jumpers and DIP switches to fine-tune their systems, paving the way for the overclockers of today with skill and a determination to wring more performance out of their systems. That spirit lives on in our coverage and in our vibrant community of enthusiasts.

You’ll see constant references to our past in our valued forums, where thousands of enthusiasts, from newcomers to veterans of 20 years or more (many who still remember setting DIP switches by hand), help the community solve vexing issues with their tech while also providing valuable insight and commentary on the latest happenings in the tech sphere.

Today, our ethos remains the same — we strive to deliver unbiased coverage of the latest technology, backed by comprehensive benchmarking to underline our conclusions, thus delivering the best possible buying advice to our readers. We now cover the full breadth of PC components and peripherals while continuing to branch out into new areas that resonate with our audience, such as 3D printing and associated products, but we’ll always remain grounded in our core areas of PCs and PC components.

Despite newfound challenges facing the publishing business, such as the rise of AI that lifts our expertise without compensation — and often without attribution — and an ever-more punishing Google landscape, we work tirelessly to stay on our current growth trajectory while developing additional new means to serve our readers, such as our Tom’s Hardware Premium service. This subscription-based service provides our readers with longer-form news, analysis, testing, and features for those who want to dig even deeper into our core coverage areas. Our service also includes access to our Bench database, which provides up-to-date benchmarks of the latest PC hardware in an easy-to-compare format.

The silicon, software, and publishing landscape have all changed dramatically over the last three decades, but our goals haven’t shifted, and yes, we still carry on with many of our old traditions. We thank you, the readers, for providing us with the opportunity to share our passion for hardware with you for the last thirty years, and invite you to join us for the next 30.

Apple will pay even more for memory in the September quarter than it did in the June quarter, CEO Tim Cook told analysts on the company's earnings call on July 30, after memory costs accounted for more than the entire sequential decline in Apple's adjusted gross margin. Cook, speaking from Cupertino on his final call before John Ternus takes over as CEO, called the market "a hundred-year flood on the memory pricing." Apple's consolidated financial statements for the quarter ended June 27 put inventories at $11.09 billion, up 87% year over year, with $5.46 billion of cash consumed building that position over nine months. CFO Kevan Parekh said the benefit Apple gets from that carry-in inventory shrinks after September.

Apple held $5.93 billion of inventory at the end of June 2025 and $5.72 billion at its September fiscal year end, so the $11.09 billion reported for June 27 is a 94% increase in nine months. The cash flow statement puts the same movement at $5.46 billion consumed by inventories over those nine months, against a $1.22 billion release in the year-ago period. Measured against quarterly cost of sales of $54.65 billion, the June position works out to roughly 18.5 days of inventory, up from about 10.7 days a year earlier. Apple has run one of the leanest working capital positions in consumer electronics for two decades, but that has now been flipped on its head.

Parekh told analysts the carry-in inventory partially offset memory costs in the June quarter and will do so again in September, with a decreasing benefit beyond that. Cook said market pricing for memory keeps rising past September and that the effect on Apple's business could grow. Erik Woodring of Morgan Stanley asked whether Apple intends to pursue multi-year long-term agreements with suppliers at pre-agreed prices. Cook answered the second half of the question, on pricing philosophy, and left the agreements question alone.

Company gross margin was 49.3% in the March quarter and 48.1% in June, once the roughly two percentage points of tariff refunds come out, Parekh said, and more than 100% of that 120 basis point decline is explained by memory costs. Apple guided September gross margin to 47% to 48%, including about one percentage point of tariff refunds, putting the adjusted midpoint near 46.5%, and Parekh attributed that step down to the same dynamic. Foreign exchange was a factor in the June quarter but not the main one.

The cost of sales for products rose 8.1% year over year to $47.15 billion, while product revenue increased 18.1% to $78.68 billion, which lifted product gross margin to 40.1% from 34.5%. The Mac and iPad price increases that came in June, the tariff refunds, and the stockpile together more than covered the memory increase in the reported quarter. On the other side of the trade, SK hynix ran a 76% operating margin over the same three months on revenue of 79.32 trillion won and operating profit of 60.54 trillion won, the company said recently, and guided third-quarter DRAM bit shipments up only about 10% sequentially. TrendForce expects conventional DRAM contract prices to rise a further 13% to 18% in the third quarter.

Cook, asked whether Apple's push for sourcing flexibility is about securing volume or protecting its price points, said the DRAM market has three suppliers and that more of them would help on the supply side and perhaps on pricing, then corrected himself to say the pricing effect is unclear. He said Apple is "evaluating all options." The fourth supplier available to him is CXMT, which the Financial Times reported in July that Apple has begun testing DRAM for devices sold in China while lobbying Washington for clearance to use its parts more broadly. Representatives John Moolenaar and George Whitesides wrote to Commerce Secretary Howard Lutnick earlier this month, asking for purchases from CXMT and YMTC to be barred outright, including through allied supply chains. CXMT listed on Shanghai's STAR Market in July.

The unit supply constraints Apple flagged for the September quarter are a separate problem from memory pricing. Cook attributed them to the availability of the advanced process nodes Apple's SoCs are built on, after iPhone and Mac demand ran ahead of the company's plan, and said they'll hit iPhone, Mac, and iPad in September, against Mac primarily in the June quarter. Apple guided September revenue growth of 9% to 11% year over year, down from 16% in the previous quarter.

In less than two years, the entire market for PC hardware has erupted into a high-priced inferno. Catastrophic might seem hyperbolic, but if you’re trying to build or buy a PC, the impact of the AI boom on prices has been immense, with costs consistently bolting upwards. Buying RAM, SSDs, traditional hard drives, and graphics cards, along with the PCs and laptops that require them, is now significantly more expensive than it was in 2024 and 2025, which makes finding a great deal an almost essential part of the process.

That’s easier said than done, of course. Like Sasquatch or the Loch Ness monster, a truly great deal on PC hardware can feel like an impossible myth. As somebody who spends their days looking for deals, however, I can say that’s not the case. There are plenty of good deals out there each week, if you know where to look and what to avoid. Here are some of the places you should be checking to find the gear you need at a better price.

Bundles, bundles, and more bundles

A component bundle isn’t a new concept; we’ve seen retailers offer combo deals that throw together various bits you’ll need to build a PC for years. Newegg’s bundle deals, however, have been a lifeline for PC builders over the last few months. If you’ve been a regular Tom’s Hardware reader, you’ll have seen a fair few of them yourself.

There’s a good reason why: value for money. Newegg’s RAM bundles, while not universally good value, allow buyers to pick up RAM at an effective cost that is significantly lower than buying it separately in many cases. While the RAM deals have been among our favorites lately, Newegg also combines SSDs, monitors, GPUs, and other components into bundles, although you’ll need to carefully review the deals to see if they’re worth the value.

Other retailers offer combo deals, too, including Amazon (in rare cases) and B&H Photo, but with less frequency than Newegg. If you need a bargain for your budget, refresh Newegg’s Combo Deals page on a daily basis, because the deals are always changing.

Microcenter is a PC bargain powerhouse if you can visit one

Microcenter often advertises deals on PC hardware that are in-store only. While this is inconvenient for those who prefer to shop online, it does mean that scalping bots can’t just hoover up any great deals on kit. You need to physically go to a store to pick up the best prices.

Like Newegg, it also runs combo deals that combine RAM, CPU, and motherboard together for a great price. You’ll also find open box and clearance stock on sale, with prices hugely marked down compared to buying new, as well as in-store exclusives that can’t be beaten via its online rivals.

The biggest problem with Microcenter is location: it has only 30 stores across the United States, with plenty of states missing out on the action. If you’ve got one nearby, however, make sure to pop in regularly to see what you can pick up.

Buying second-hand can sometimes save your money

Buying used isn’t always a bad idea. While plenty of second-hand scams exist, if you’re savvy with your purchases, you can save money on building or upgrading your PC. This is especially true for the components that require a little less care, like cases, peripherals, fans, and coolers.

You don’t need to buy from individual sellers to do this, either. Certified refurbished hardware, straight from manufacturers or trusted third-party resellers, can also get you a tidy discount on parts or full-blown builds. Woot, Amazon’s budget marketplace, is a great place to find sales on refurbs from brands like MSI and Dell on a regular basis. Some brands also offer their own refurbished products, including Apple, which offers up to 15% off and includes an additional warranty.

Don’t dismiss the private sellers, but make sure you use your best judgement if you decide to buy gear this way. Our full guide on buying second-hand PC hardware will help you bypass the scams.

Woot is Amazon, but cheaper

Woot is a website that, as a deals writer, I check on a daily basis. As it's owned by Amazon, you can take some assurance in the fact that the company isn’t just going to go bankrupt overnight. It’s a tried and, for many people, trusted retailer.

That’s not why I like Woot. I like Woot because it’s cheap. You can pick up serious bargains on PC hardware at Woot. Laptops, PCs, peripherals, and components can all be found at varying discounts, some as high as 75-80% compared to their highs. The deals aren’t universally great, but when they’re good, they’re good. A good example is with RAM, where we’ve seen DDR5 RAM kits drop $70-100 below anything you’ll find elsewhere.

As with all good discount warehouses, the deals on Woot will ebb and flow. Sales on certain brands will appear and disappear. The best deals will sell out in hours, if not minutes. If you’re planning a build or upgrade, make sure to look at Woot first.

Check the price before you buy

A huge price cut can seem like the deal of the century, but don’t be fooled. You need to perform due diligence on deals before you jump in, even if you’re being bombarded by ‘limited-time only’ labels. This can let you narrow down a shortlist of products to buy or, in some cases, force you to change your plans and look at buying another product entirely.

Unfortunately, most retailers aren’t hugely open about their historical pricing for products, so you have to look elsewhere. A good tool to keep in your arsenal is Camelcamelcamel, which gives you historical price data for products sold on Amazon. The graphs allow you to see immediately how good a ‘discount’ really is.

For example, Amazon has an LG monitor listed on sale right now. Camelcamelcamel’s data shows that the price has steadily dropped since it launched, from as high as $850. The most recent Camel data shows a price of $484.99, but the new price, $399, is a new record low. That’s a deal worth grabbing, and Camel’s data makes it easy to understand.

Use Newegg’s PC Builder to help you put together a bargain build

Other PC building sites exist, but I like Newegg’s custom PC builder tool. It lets you find all of the parts you’ll need for different projects, whether it’s a 4K gaming PC or a budget 1080p rig, and gives you the immediate price you’ll need to pay. In some cases, it’ll also apply additional combo discounts, as well as extra coupons, to help you bring the prices down further.

It works in a few different ways, depending on how comfortable you are putting a build together. You could start by selecting your individual components. I’d probably start by picking out my CPU first, as this will help you determine the type of RAM you’ll need, as well as the motherboard.

If that seems too difficult, you can use Newegg’s AI search to put something together for you, or use the popular ranked builds, with all of the products you’ll need grouped together. The ranked builds are useful, as they can give you an idea of the type of build you can get for your money right now. If it’s too high, you can always mix-and-match by buying new with used, or by carefully picking up deals as you go.

Patience, luck, and compromise

Unfortunately, you can’t go back in time to 2024. PC hardware is more expensive now than it was, and with the AI revolution showing no signs of stopping, that’s unlikely to change for the time being. If you can’t stick with your existing rig, a great deal on an upgrade could be your only option, as long as you don’t rush out your build.

The limiting factor, of course, is that you might end up paying more if you wait around. There isn’t a way around that. Components are getting more expensive, but if you follow these rules, you should find reasonable deals pop up each week. Some weeks do feel slower for deals, most noticeably before or after a big sales event like Black Friday, but that doesn’t mean they stop completely.

You’ll have to compromise, however. 2024 and 2025 pricing is long gone. That’s a hard, bitter pill to swallow for all of us. Judgmentally, you’ll need to look at the value of products right now, not three or six months ago, and decide whether you’re comfortable with the prices on offer. With luck, you’ll find some of the diamonds in the rough.

Lumentum CEO Michael Hurlston told an audience at the RAISE Summit in Paris earlier this month that indium phosphide, the compound semiconductor behind every laser in an AI data center, is heading into a supply squeeze worse than what we've already seen with DRAM / NAND, and that Nvidia's decision to fund Lumentum and its biggest competitor at the same time was a response to exactly that.

In his remarks, Hurlston said that telecom customers bought lasers in the hundreds, while Nvidia and the hyperscalers are asking for hundreds of millions. While Lumentum runs five indium phosphide fabs, it's still shipping more than 30% below what customers want. Nvidia's answer, in March, was to write $2 billion checks to Lumentum and Coherent, the two suppliers that, between them, make most of the world's high-speed datacom lasers, with purchase commitments and future capacity access attached to both.

"Between the two of us, I don't think we can service the demand that Nvidia and others are now putting on us to solve this resistance problem in the data center," Hurlston added.

Silicon doesn't emit light

Indium phosphide has a direct bandgap of roughly 1.34 eV, which lets it convert electrical current into photons efficiently. Silicon's bandgap is indirect, so it can guide, split, and modulate light but can't generate it. Every silicon photonics platform in production, including those of Nvidia, Broadcom, Marvell, and Cisco, still needs an indium phosphide laser somewhere in the package to supply the light for silicon to manipulate. Moving from pluggable transceivers to co-packaged optics changes where that laser sits and how it's mounted, but it doesn't remove it from the bill of materials.

Nvidia's marketing claims its photonics switches use four times fewer lasers than an equivalent pluggable deployment, alongside 3.5 times better power efficiency and ten times better network resiliency, all of which are vendor figures. Those savings are per port, and it's that port count that's exploding.

The high-end Spectrum-X Photonics configuration runs 512 ports at 800 Gb/s for 400 Tb/s of switching, and Quantum-X Photonics InfiniBand runs 144 ports at 800 Gb/s. Co-packaging also shifts the laser type toward high-power continuous-wave sources and external laser modules that feed multiple channels, which are harder to build than the electro-absorption modulated lasers inside a conventional pluggable. Coherent's Nvidia agreement covers that category of high-power CW lasers, external laser source modules, and fiber array units.

Capacity at Lumentum and Coherent

Lumentum posted record revenue of $808.4 million in its fiscal third quarter, up 90% year over year, with components revenue of $533 million and pump laser shipments up 80%. On the May earnings call, Hurlston told analysts the company expects its supply line to increase 50% measured from one December quarter to the next, and in the same breath said the supply-demand imbalance on EMLs had widened from the 25% to 30% given a quarter earlier to "somewhere greater than 30%," with pump lasers tighter still. A supplier growing output by half a turn per year and losing ground anyway is a clean measure of how steep the demand curve is.

Coherent's 6-inch indium phosphide line yields more than four times as many devices as its 3-inch line at less than half the cost, CEO Jim Anderson told investors on the company's fiscal Q3 call. Anderson said EMLs, CW lasers, and photodiodes are all in production on the 6-inch line with yields above the legacy 3-inch lines, and that internal capacity would double by the end of the June quarter, one quarter ahead of plan, then more than double again by the end of 2027. Coherent's revenue hit a record $1.8 billion, up 21%, with data center and communications now 75% of the total against roughly 41% a year earlier, and backlog stretching into 2028.

Logic and memory moved to 300mm wafers in the early 2000s. Indium phosphide is a brittle, expensive, small-boule material where the industry-wide upgrade currently underway is 3-inch to 6-inch, roughly the transition silicon completed in the 1980s. Lumentum's fifth fab, announced in March, is a converted Qorvo gallium arsenide plant in Greensboro, North Carolina, described as 4-inch and 6-inch compatible and ramping around 2028.

Running through China

Indium is recovered as a byproduct of zinc refining, so its output can't be scaled independently of zinc economics, no matter how much laser demand there is. The USGS Mineral Commodity Summaries 2026 put China at an estimated 760 tonnes of roughly 1,100 tonnes of global primary refined indium in 2025, about 69%, and recorded a 72% year-over-year fall in unwrought indium exports between September 2024 and September 2025 after Beijing placed the metal under export controls in February last year. The U.S. warehouse price averaged about $390 per kilogram in 2025 against $340 in 2024.

AXT's Chinese subsidiary Tongmei had to obtain Ministry of Commerce export permits, granted in June and August 2025, before it could resume shipping indium phosphide substrates out of China. The fabs Nvidia is funding sit downstream of that licensing regime, and the wafers going into them aren't made in the United States in meaningful volume.

DRAM contract prices rose 90% to 95% quarter over quarter in Q1 2026, the largest quarterly increase TrendForce has recorded, and the firm forecast a further 58% to 63% in Q2 with NAND up 70% to 75%. HBM is sold out for 2026. Hurlston is measuring his warning against a genuinely historic crunch, which makes it a strong claim rather than a throwaway one, and he runs a company whose valuation depends on the shortage persisting.

LightCounting's April 2026 market forecast puts current transceiver demand about 30% above supply, matching Lumentum's own figure, but states that the shortages should be gone by the end of 2026 and cuts expected Ethernet transceiver growth to 65% for the year after 82% in 2025 and 93% in 2024. Coherent, hitting its capacity doubling a quarter early, points the same way. The distinction from memory is that the fix here is a wafer-size transition already running in production with yields ahead of the old node, not a new fab that takes three years to build.

A developer has created a proof-of-concept data transfer system that shuns any dedicated app requirement and neatly sidesteps mandatory networking, pairing, or giving permissions beyond camera access. Instead, the method transmits information between devices by streaming data via rapidly updating QR codes at up to 60 FPS via the browser your smartphone already has. The test info shared by developer bashalarmistalt on GitHub backs claims that these transfers can run at up to 190 KB/s. This low-friction two-device screen-to-camera data transmission technique is dubbed Decimen Optical Transfer: fountain-coded QR file transfer.

Had an idea for air gapped file transfer, able to get 120 KB/s from r/vibecoding

The GitHub project is linked to by Redditor Alstroph, who seems to be the same person. We’ve chosen to embed the Reddit post about the Decimen Optical Transfer solution above, as it includes an illustrative video of a QR code-driven data transfer.

Bashalarmistalt/Alstroph says they used Claude Code to build this cached web app, which simply runs on both smartphones within the browser, with camera permissions given. They explain that they came up with the idea behind Decimen Optical Transfer to create “a phone-to-phone file transfer option without requiring the phones to be on the same network.” After a modicum of chin stroking, they settled upon the possibility of using “rapidly flashing QR codes” to brew up this proof-of-concept.

Far more detailed information about the project is available in the GitHub repository, linked above. There we also read that the use of ‘fountain codes’ was instrumental to the technique, ensuring missed frames and retransmission quirks don’t hinder the data transfer process. Also, it is explained that every streamed QR code frame is self-describing, as a “20-byte header carries the session ID, sequence number, block count/size, file length, and a hash.”

Hints are provided for tuning Decimen Optical Transfer performance with the PoC solution. The dev used an iPhone and the Apple ProMotion camera with stacked codes; they achieved ~128 KB/s handheld data transfers. The data rate could climb to ~186 KB/s speeds if both the sender and receiver devices were positioned absolutely stationary.

The Decimen Optical Transfer software is distributed under the generous MIT license. Bashalarmistalt is aware that there have been several prior projects but asserts the concept behind their Claude Code-aided solution was arrived at independently. We’ve also covered QR code-based data storage tech numerous times. For example, Cerabyte famously uses microscopic QR codes for its ultra-long-life ceramic storage.

Thunderbolt docks are an easy way to expand the number of available external ports for a laptop and have become quite popular in recent years. They are particularly beneficial with the best ultrabooks, which can sometimes be equipped with as few as just two Thunderbolt ports and no additional external ports for connectivity.

We’ve previously taken a look at some popular Thunderbolt 5 docks, with some costing as much as $650. This time around, we’re looking at some more affordable solutions, with all three of these units carrying a street price of less than $400. The UGREEN Revodok Maxidok has a street price of $389.99 after coupon, while the Plugable TBT-UDH2 and Keychron TB5D-1 are both available for around $350.

Plugable TBT-UDH2

The Plugable TBT-UDH2 is a relatively compact Thunderbolt 5 dock that feels absolutely solid with its weighty aluminum chassis. The BT-UDH2 is designed to stand vertically (confirmed by the rubber feet at the base of the unit). However, there’s no reason why you wouldn’t be able to lay the unit on its side if you wanted to.

As for actual ports, the TBT-UDH2 has two USB-C ports up front (one of which supports 30W PD), a single USB-A port, microSD and SD card slots, a 3.5 mm headphone jack, and a single downstream Thunderbolt 5 port (30W PD).

Moving to the rear of the unit, there are two more USB-A ports, three additional USB-C ports, two HDMI 2.1 ports, a 2.5 GbE port, and a Thunderbolt 5 upstream port for your laptop. And here lies my main complaint with the TBT-UDH2: it only has one downstream Thunderbolt 5 port, and it’s on the front. I would have liked to have seen at least two, with one on the front and one on the back. At this price point, having just one downstream Thunderbolt 5 port seems like a big miss.

Keychron TB5D-1

The Keychron TB5D-1 is the other $350 Thunderbolt 5 dock assembled here today. It is similar in size to the Plugable dock, but is finished in natural aluminum. Keychron includes rubber feet on the bottom and one side of the dock, encouraging you to operate in either a vertical or horizontal orientation.

You’ll find two USB-A and one USB-C port on the front, along with microSD/SD slots and a 3.5 mm headphone jack. Moving to the back, you’ll find two additional USB-A ports, two HDMI 2.1 ports, two downstream Thunderbolt 5 ports, and a Thunderbolt 5 upstream port for the host PC. For networking, there’s also a 2.5 GbE port.

UGREEN Revodok Maxidok

The UGREEN Revodok Maxidok is the most expensive Thunderbolt 5 dock here, with a street price of around $390. However, you do get some added functionality for the $40 price difference. At first glance, the Revodok Maxidok looks like a Mini PC with its square-ish form factor. The aluminum body is finished in a combination of dark grey (upper half) and copper (bottom half).

Unlike the other two docks, the Revodok Maxidok has an internal cooling fan mounted inside to help keep the electronics cool (Thunderbolt docks are notorious for their heat output). During normal operation, I couldn’t hear the fan running. I could only just barely hear it if I stuck my ear to the side of the docking station (which is, of course, not a typical usage scenario).

The front of the docking station houses microSD/SD slots, three USB-C ports (two of which support a total of 60W PD), and a 3.5 mm headphone jack. On the back, you'll find three USB-A ports, two more 3.5 mm audio ports, a DisplayPort 2.1 connector, two Thunderbolt 5 downstream ports, and one Thunderbolt 5 upstream port.

The Revodok Maxidok also has one hidden feature. If you flip the dock over, it has a cover that's held in with one screw. Remove the screw, and you'll find an M.2 slot for adding an internal SSD (up to 8TB in capacity).

Thunderbolt 5 Dock Specs Comparison

Thunderbolt 5 Dock SSD Performance Testing

We tested SSD performance of the three docks using a 1TB Micron 2500 Series PCIe 4.0 SSD (MTFDKBA1T0QGN-1BN1AABYY). The SSD is rated for sequential read speeds up to 7,100 MBps and sequential writes up to 5,800 MBps.

For baseline performance numbers, I tested the Micron 2500 using the onboard PCIe 5.0 M.2 slot on an Asus Z890 Creator WiFi motherboard. For testing with the Keychron TB5D-1 and the Plugable TBT-UDH2, I used an Orico Thunderbolt80G enclosure with the Micron 2500 – it supports up to M.2 (PCIe Gen4x4) SSDs. The enclosure was plugged into one of the Z890 Creator WiFi’s two Thunderbolt 5 ports. For the UGREEN Revodok Maxidok, I used the native M.2 PCIe 4.0 slot with the Micron 2400.

Using the Micron 2500 SSD and Asus Z890 Creator WiFi motherboard as a baseline, we saw 6,674.53 MBps reads and 5,628.61 MBps writes. Of the three docks we tested with the Micron 2500, the Revodok Maxidok was the fastest with its native M.2 PCIe 4.0 slot. It achieved 5,780.54 MBps reads, roughly 300 MBps ahead of the other two.

The Keychron TB5D-1 and the Plugable TBT-UDH2 put up nearly identical numbers using the Orico Thunderbolt80G enclosure, with around 5,400 MBps reads and 4,200 MBps writes.

All three docks had no trouble maxing out the 2.5 GbE port using iPerf3, and I didn't run into any compatibility problems running my 49-inch 240 Hz DQHD monitor using the docks via HDMI or DisplayPort connections.

While all of the docks were warm to the touch, the Revodok Maxidok was noticeably cooler thanks to its internal cooling fan.

Bottom Line

Of the three docks that we tested, the one that I felt was the most versatile and worthy of a place on my desk is the UGREEN Revodok Maxidok. It’s the only one of the docks with a native DisplayPort 2.1 connector and the only one with an internal M.2 SSD slot. In addition, it offered ever so slightly faster storage performance than using an SSD with a Thunderbolt 5 enclosure. And with a street price of $390, you’re only paying a $40 premium over the other two docks.

If you prefer having two additional HDMI 2.1 ports at your disposal, the Keychron TB5D-1 is a good option as well. All of the Keychron’s USB-A and USB-C ports are 10 Gbps, while the Plugable TBT-UDH2 gives you a mix of 10 Gbps and 5 Gbps USB ports. In addition, the Keychron dock features two downstream Thunderbolt 5 ports, while the Plugable only has one.

Additional Thunderbolt 5 Docks to Consider

Although we plan to keep this guide updated as we test additional Thunderbolt 5 docks, here are some additional units to consider:

• UGREEN Thunderbolt 5 Dock – $274.99
• Ivanky FusionDock Max 2 – $379.99
• Anker Prime Thunderbolt 5 Dock – $319.99
• Kensington SD50000T5 Thunderbolt 5 Dock – $194.99
• CalDigit E5 Thunderbolt 5 Dock – $249.99

The Steam Machine helped grow the popularity of Linux gaming, including installations of Bazzite and other gaming-oriented Linux distributions. Valve seemingly doesn't want to stop its open-source development efforts anytime soon, and is now working on a port of the Mesa Radeon Vulkan driver (RADV) to Windows; It's already running Counter-Strike 2, according to developers at Collabora.

As cross-platform development is rather tricky, Valve opted to get a port of RADV to Windows going by way of sponsoring contractors at Collabora. In its blog post, Collabora explained the several hoops it had to jump through to accomplish this task.

With Windows 10 and WDDM 2.0, Microsoft improved the split between graphics drivers' userspace code (the vast majority of the driver itself) and the kernel-level portion that actually talks to the graphics card. This presented the opportunity to hook RADV to the AMD kernel card driver. That's easier said than done, however, as communication between those parts often carries non-standardized data that RADV needs to understand. And to understand the "conversation," it needs to be recorded and analyzed.

An earlier 2024 effort by Faith Ekstrand yielded a basic-but-valuable utility for logging WDDM 2.0 calls and reverse-engineering them to produce a basic RADV implementation. Out of both debugging necessity and as a development tool, Collabora built and expanded upon Ekstrand's work, improving the logger to the point where it can now fully analyze any Vulkan application that runs with AMD's official driver and dump all the data passing to the kernel.

After a lot of work getting to grips with how the AMD driver interacts with the kernel driver, including but not limited to reverse-engineering obscure data structures, the team made progress, and Windows RADV is now able to run some games, including Counter-Strike 2.

Despite the ongoing effort, Collabora explains that since user- and kernel-space driver are a matched pair, changes to those aren't guaranteed to be backwards-compatible, meaning that even a fully functional RADV could break at any point. For that reason, Collobora is requesting that AMD, Microsoft, or both provide a documented interface to the kernel driver or an intermediary compatibility layer.

AMD graphics driver development on Linux has coalesced around the Mesa Vulkan stack, with both company and community devs contributing to the RADV project. Over in the Windows world, the only option is AMD's proprietary driver, which can cause a lot of headaches when developing cross-platform games and applications.

AMD's Vulkan driver for Windows has developed a reputation for instability. Meanwhile, Linux RADV is generally praised for its stability and performance, sometimes running faster than the AMD Windows driver, especially on older cards. With a rapid development schedule, it also generally sees fixes and speed upticks often.

If at some point using RADV on Windows becomes viable, you'd be getting an arguably more stable, mature driver with active development. Games' graphical issues could become far easier to debug and patch thanks to the open nature of RADV, and studios developing with Linux in mind can target the one platform instead of two with different behaviors. Any developer or company can contribute to the project, too.

Furthermore, this lets Valve improve Windows compatibility layers, and any optimizations can be carried over to both operating systems. All told, this is likely one of the several moving parts to improve Linux — thus the Steam Deck, Steam Machine, and upcoming hardware — as a viable gaming platform. Even a future notion of gamers installing RADV on Windows to get a performance or stability boost isn't too far-fetched.

Additionally, RADV on Windows would also help keep discontinued cards usable, and given pricing right now, that certainly would be a good thing.

Unless you’ve been living under a rock, OpenClaw has dominated headlines, both good and bad, for much of early 2026. Developed by Peter Steinberger, the tool is an engine that spins up an AI agent that can autonomously act on your behalf, going so far as having the ability to run files, browse the web, and much more. Using a system named “Skills,” you can even teach your AI assistant to perform new tasks, with more integrations popping up daily. But how useful is it for the average person? I took it upon myself to answer that question by using the relatively humble Beelink SER10 MAX mini PC, which comes pre-installed with OpenClaw, to find out.

To kick things off, when setting up your OpenClaw installation, there’s a fairly large decision one has to make: Do you want to rely on Cloud resources and more powerful AI models, or run something locally? Beelink’s SER10 MAX ships with Qwen-3.5 9B, which is a relatively older and more outdated AI model. Since I want to keep things fairly simple, I opted for the local AI route first. To run larger models, you’ll need a lot of memory, so I first tweaked the humble Mini PC’s video memory up to 48GB, which should allow us to keep a larger, more complex model in memory. It also leaves us 16GB of system memory to play around with, which should be more than enough to run the terminal and ensure that everything else works as intended.

Selecting the ideal local AI model

Having 48GB of available video memory should allow us to run a fairly powerful AI model on the system. However, the downside of running a larger model is that token speeds are likely to be slightly lower than expected. However, for running the super-smart AI that does things for us locally, we want as much intelligence as we can get. For this exercise, I chose Google Gemma 4 31B (UD-Q8_K_XL), a near-lossless quantization, somewhat ambitiously, as I will learn shortly.

After downloading the model and running it in llama.cpp, we managed to attain 2.34 tok/s. On average, everyday queries took 116 tokens to generate, at 2.34 tok/s. That’s still too slow for fast everyday use. So, I took a deep breath and conceded that the humble Ryzen AI 9 HX 470 didn’t have fast enough memory or memory bandwidth to run such a large model at acceptable token speeds. Even if I had dropped the quantization to 4-bit, we’re still looking at the theoretical maximum of around 5 tok/s for that model in particular. If you had a faster machine with rapid RAM speeds, such as a Strix Halo system like the Framework Desktop, it might be more workable, but for a lower-end piece of silicon with relatively humble DDR5-5600 speeds, you’ll just have to accept a slightly more neutered model.

So, I eventually conceded that the smaller Gemma 12B (Q4_K_M) was a much more sensible choice for a device of this caliber. After loading things up into llama.cpp, we managed to get a much more sensible 10.64 tok/s on a general knowledge query: “What is Tom’s Hardware?” Now that I have a little piece of talking electrified sand on my desk, it’s time to configure OpenClaw.

Hatching HammerClaw

The device I am using, the Beelink SER10 MAX, comes with OpenClaw pre-installed. The only real dependency it has is llama.cpp, which we configured earlier while testing which AI model to use. Since the llama.cpp port is open, OpenClaw leverages that to talk to the AI model, with all of its additional fanciness included. The OpenClaw installer is fairly straightforward in getting things up and running, including setting up a Telegram channel to communicate with our AI model remotely and configuring a gateway, so we can configure things without relying on Ubuntu’s terminal commands.

Within the installer, we start to define our new AI assistant: It asks what its name and identity are, some basic details about the user, as well as what principles it should uphold, in a very extravagant file named SOUL.md. Remember, our talking sand isn’t alive, so it’s all quite dramatic. Generating a SOUL.md file takes a while for our humble local AI model, which I’ve named HammerClaw. But can it do anything useful for me to justify its nascent AI existence? Right now, it’s taken five minutes to think about exactly what it is and what it’s doing.

After a little while, our little HammerClaw “hatches,” asking what its purpose is, who I am, and how it should talk. Personally, I don’t like it when AI models are verbose, so it’s straight and to the point, and should never, ever lie to me. When AI models can scale to rather humble devices like this one, the smaller, less-intelligent models can be error-prone. With our little local AI agent alive and kicking, it’s time for it to automate a task for us; it couldn't be that difficult… right?

Stumbling blocks

HammerClaw quickly wakes up, and I offer it a task: to gather ten news articles from trusted outlets and different parts of the day, ensuring freshness, with a small digest of what’s happened. Since most of my work on Tom’s Hardware Premium is centered around chipmaking and data centers, I want it to focus on those topics. HammerClaw then quickly takes the task and starts working out how to pull it off. It’ll use its built-in cron tools and felo-search to pull stories from the internet.

Now, here’s where things go bad for poor HammerClaw. It then begins to simulate the action, instead of actually performing it, despite saying that it had set up the cron jobs and skills required for the automated scheduling. Even worse, it hallucinated a list of links that went absolutely nowhere. After pointing the error out, it gets apologetic and investigates why things went wrong. As it turns out, some additional parts need to be configured, which it tried to do and failed once again. Agentic Tool use is now a specific benchmark, but when asking Gemma 4 12B to set up a multi-step task like this, it simply couldn’t manage with the conversational tone of my prompts.

It’s at this point that I asked HammerClaw to give itself a grade, to which it offered itself a B- on accuracy for hallucinating and making up news stories. Now, I don’t want to say that all OpenClaw AI agents would do this, as we are running a relatively light local model. I would expect that larger local models would be able to identify what they need to do much more efficiently due to having a significantly higher model parameter count. With that in mind, I wondered if another AI model could help HammerClaw along a little bit with this task. And so, I went onto my OpenRouter account and opened a chat with the big, beefy 2.8 Trillion Parameter Kimi K3.

Kimi K3 saves the day

Comparing a cloud-based frontier model like Kimi K3 and Gemma 4 12B just isn’t fair. One takes up terabytes of RAM to run, while Gemma fits inside a Mini PC that lives on my desk.

Instead of using Kimi K3 to run the AI itself, I tasked it with actually helping me set up the job that HammerClaw seemingly didn’t have the skills to pull off. This hybrid workflow – of using a local LLM in tandem with a more powerful one in the cloud- is a common setup for many AI enthusiasts. After about a dollar in tokens, it sent me a list of OpenClaw commands, skills, and instructions, after reading the current documentation for OpenClaw CLI to ensure it got everything right. It was flawless. I followed the instructions Kimi K3 gave me and entered them into an Ubuntu Terminal, where it successfully created a new skill for HammerClaw named ‘News-Intel,’ instructed me on how to enable the web-search functions, and set up the Cron jobs for the automated sends. Bearing in mind that I had never used OpenClaw before, it was all surprisingly smooth, even if our local model couldn’t do all of these tasks itself.

With everything set up, the buck is then passed back to our much humbler Gemma 4 12B model-powered HammerClaw to execute the rest – after all, this is supposed to be a test for how Local AI models function. I executed the command for a manual run while checking the operational logs, where it was successfully calling all of the tools, and thought, against all odds, HammerClaw might actually be able to do it. A few minutes later, I received a Telegram message. HammerClaw had managed to locally execute the task and send me a digest of ten news stories.

Of all of the things to automate, this is likely one of the simplest examples of how someone can use OpenClaw. While simple, it’ll also save me a bit of time every day staring at an RSS feed and looking for stories myself. But, it’s quite a distance away from the “speak, and it’ll do whatever you want it to!” promise that drew so many into a frenzy earlier this year.

Is it worth it for the average person?

If all you heard about OpenClaw is that it’s a magical AI agent that can do anything, as I’ve learned, it’s not quite the truth. Unless you’re well-versed in several elements, like understanding model choices and getting your head around what models perform well for tool-calling. Running a humble local setup might be fun, or interesting to tinker around with, but the true power for Local AI developers and tinkerers lies with the obvious: More power to run bigger, complex models, and more agents running tasks consecutively. In fact, we’ve taken a look at how these workflows can be used in practice with a mixture of Local and Cloud AI models for Tom’s Hardware Premium.

The issue here is that for our local model, this simple task – of running and sending us 10 news stories- could not set itself up, and that’s using hardware that already costs north of $1,500. As our resident local AI expert and GPU guru Jeff Kampman has recently tested, for those serious about AI who want real power without relying on the cloud entirely, you might want to save up your pennies to run stronger, faster local models, either using dedicated GPU-accelerated setups, or dedicated boxes such as the DGX Spark, or a cluster of Dell Pro Max GB10s, both of which will cost you north of $5,000. You’d hope that the models capable of running on that hardware wouldn’t fumble the setup of a relatively simple Cron job.

The real question is, will having a local AI inference box meaningfully change how you work, or the work you do, to pay for itself? For many, that’s the lingering question that many are asking themselves. For now, HammerClaw is sending me more articles every few hours, a task that can be performed by simple scripting. But the manual “sift” is being handled by an LLM. As neat as it is, I wouldn’t pay $1,500 for the privilege. Luckily, it’s not merely a box made for AI inference; there’s a whole computer attached.

We're quite familiar with Sovol 3D printers around these parts, having reviewed several models over the years and finding that pretty much all of them produce high-quality prints. The company is now stepping up its game with the Sovol M1D, an open-source, independent dual-extruder (IDEX) printer with two nozzles and seven toolheads, a maximum print volume of 300 x 300 x 350 mm (11.81" x 11.81" x 13.78").

This bit o' kit can operate its nozzles in true independent mode (rather than alternating between them), letting users copy prints for easily printing duplicates and mirror them for doing left-right versions. In multi-head mode, each nozzle can output a different material. The first nozzle has a fixed toolhead, while the second can swap between heads independently. The open-source nature of the printer ought to let it be easy to mod, and as expected, it relies on the OrcaSlicer software by default rather than proprietary software such as Bambu's offerings.

The M1D comes in two variants, Essential and Advanced, with the higher-end model having the same basic specs but coming in a heated enclosure that keep inside air at 60°C (140°F). Sovol says each nozzle can print at up to 600 mm/s, and accelerate at 10,000 mm/s². The nozzle-and-toolhead interface seems quite nifty, as the M1D ought to swap toolheads in just five seconds, and keeps the standby heads warm so they're ready for printing the second they attach to the nozzle. One of the heads is fixed, and the other six are interchangeable.

The combination of the speed and tool-swapping technology has Sovol claiming the M1D can perform multi-colored prints five times faster than "others," displaying what appears to be a Bambu P1S in the comparison pictures. Likewise, said multi-color or multi-material prints supposedly produce "almost zero waste."

The M1D has a number of measures to prevent failed prints, including automatic bed leveling with nozzle Z-axis compensation thanks to an eddy current sensor, X/Y nozzle cameras, vibration compensation, and a 720p chamber camera that will have AI obstruction and spaghetti detection in a future firmware update.

The seven toolheads allow for easily integrating water-soluble materials for printing sacrificial supports and molds, movable mechanisms, and hollow parts, while the enclosure of the Advanced version lets the M1D print particularly resistant materials like ASA (acrylonitrile styrene acrylate), PA (polyamide), and PC (polycarbonate).

The Sovol M1D is available through a Kickstarter project that's already pulled in over $2.8 million — many times over the initial $191,254 goal. Buying into a crowdfunded project frequently elicits concern, but Sovol's track record has historically been pretty good. With early bird pricing and not accounting for shipping costs, the M1D Essential goes for $1,299, while the Advanced version with the heated enclosure costs $1,599. The printers are expected to start shipping in November.

There’s been a shift toward using a single DIMM of DDR5 to skirt the worst of the RAM pricing crisis. AMD has suggested to us previously, at least, that it’s an option PC builders are exploring, and it’s a wrinkle that’s shown up in dozens of prebuilts; one that we’ve been careful to avoid when recommending products, particularly during peak shopping events. But just how much gaming performance are you giving up with a single DIMM when using one of the best CPUs for gaming?

The conventional wisdom is that you’re giving up quite a bit of performance, resting on the ideas of previous DDR generations, where going down a single stick will cut your bandwidth in half. The same is true with DDR5, but things are a bit messier, which we’ll dig into later.

At a high level, using a single DDR5 DIMM doesn’t compromise gaming performance by nearly as much as you might expect. We saw drops of around 8% to 10% across Intel and AMD CPUs, and less than a 5% difference with AMD’s Ryzen 7 9800X3D.

A proper dual-channel configuration is still the way to go for optimal performance. However, our testing shows that even a single DDR5 DIMM offers superior performance to dual-channel DDR4 on CPUs that support both memory generations.

Using a single DIMM isn’t ideal, and it brings up compatibility issues if you plan on adding another DIMM down the line (another area we’ll touch more on in-depth later). But as a stopgap measure amid surging DRAM prices, a single DIMM of DDR5 holds up surprisingly well in gaming scenarios, and it represents a nice on-ramp into a DDR5 platform while prices are out of control.

Testing single-DIMM DDR5 in games

The geomean below speaks for itself. Moving down to a single DIMM drops some performance, but it’s not nearly as stark as I expected. There are some important notes about how we tested before dissecting the results, however.

As usual, we tested at 1080p with a mixture of High and Ultra settings, using Nvidia’s RTX 5090 Founder’s Edition to minimize the influence of the GPU. That’s even more important here, as we’re not evaluating CPUs but the memory that feeds the CPU. We're looking at a separate GPU and CPU here, as well; dual-channel memory is vital if you're using an iGPU.

We also wanted to create a realistic testing scenario. Assuming you’re going for a 2x16GB configuration, that means starting with a single 16GB DIMM, not a 32GB one. That’s what we did here. Our single-DIMM configurations run with just 16GB of memory, while dual-DIMM configurations run with 32GB. Capacity isn’t a major limitation for our testing here, though it will pose performance issues if you’re running several applications alongside your game.

The Ryzen 5 7600X was our biggest loser, dropping 10.9% of its average performance across our 13-game geomean with a single 16GB DIMM. The Core Ultra 7 270K Plus, meanwhile, dropped 8.7% of its average performance, while the Core i5-14600K similarly dropped 8.3% of its performance. The 1% lows are especially notable here, scaling with average performance rather than falling off a cliff.

Unsurprisingly, the Ryzen 7 9800X3D fared the best, dropping just 2.8% of its performance on average. As you’ll see through our individual game tests, the Ryzen 7 9800X3D shows identical performance with two DIMMs and a single DIMM in multiple games. The large and speedy L3 minimizes the impact of using a single DIMM, giving AMD’s 3D V-Cache CPUs another notch in their belt (as if they needed another).

Our other geomeans don’t say much. A single-DIMM configuration consumes a few watts less, leading to slightly lower efficiency when balanced against the lowered performance.

007 First Light, the newest game in our test suite, shows good scaling across our test pool, so it’s a good place to start. The Core Ultra 7 270K Plus dropped 8.9% of its performance with a single DIMM, while the 9800X3D dropped 6.5%. The 14600K is worth highlighting here. A single DIMM lost us 7.9%, but that’s still better than dual-channel DDR4, and by a decent 6.8% margin.

This trend is fairly consistent, too. Starfield is punishing for single-DIMM configurations, with the 14600K losing 10.6% of its average performance. Even then, a single DDR5 DIMM is 6.9% faster than dual-channel DDR4. Intel platforms can scale up to high data rates, and we use 7,200 MT/s for Intel chips. With slower speeds, the performance will equalize. Still, I’d strongly consider a single DDR5 DIMM if you’ve been eyeing an LGA 1700 platform with DDR4, assuming you’re primarily focused on gaming.

Starfield shows the benefits of 3D V-Cache in this single-DIMM configuration clearly. While the performance losses with other CPUs are brutal in this title, the 9800X3D dropped just a few frames, a 1.6% decrease in average performance.

Doom: The Dark Ages is similarly harsh on single-DIMM configurations. The Ryzen 5 7600X dropped 17.3% of its average performance, and the 270K Plus fell by 14%. The 9800X3D holds up well, however, with just a 4.2% average performance loss. Marvel’s Spider-Man 2 (in the gallery below) shows a similar dynamic.

However, the addition of 3D V-Cache mainly helps in these games where we see bigger losses with other CPUs. There are several games in our suite where the performance loss between a single DIMM and dual-channel configuration was minor, particularly in GPU-heavy titles. The Last of Us Part One shows that in action.

Similarly, the performance loss is minor in Counter-Strike 2, just a handful of frames even north of 600 FPS. Even the Core i5-14600K, which was hit the hardest by far, dropped just 5.9% of its average performance (and it’s still faster than a dual-channel DDR4 configuration).

You can browse the results of the other games we tested in the gallery above, though they tell much the same story as the titles we highlighted. The two biggest learnings from this testing are that a single, fast DDR5 DIMM often outpaces dual-channel DDR4, and that AMD’s 3D V-Cache can smooth over the rough edges of using a single DIMM, particularly in those memory-sensitive titles.

How we tested

We tested on our normal test bed that we use for CPU reviews, with the only difference being dropping one of our DIMMs. As usual, we enabled XMP/EXPO for testing, both on single- and dual-DIMM configurations, opting for higher speeds on Intel platforms. AMD’s sweet spot is around 6,000 MT/s.

The data rate is noteworthy for the DDR4 comparison, in particular. With slower DDR5, we expect the delta between dual-channel DDR4 and single-DIMM DDR5 to decrease.

In addition to enabling XMP/EXPO, we disable Virtualization-Based Security (VBS), enable Resizeable BAR, and disable any automatic overclocking features that aren’t covered by warranty, including AMD’s Precision Boost Overdrive and Intel’s Extreme performance profile.

Complexities of DDR5

DDR5 has much higher data rates compared to DDR4 (2x or more), and that’s the result of significantly more complexity on DDR5 DIMMs compared to DDR4. Notably for this testing are the two 32-bit subchannels of DDR5, as well as enlarged prefetch and bank groups. You are getting half the total bandwidth with a single DDR5 DIMM, absolutely, but it’s a little more nuanced than simply running your memory in a single-channel configuration.

DDR4 uses a single 72-bit channel, and 64 of those bits transfer data (the additional 8 are for ECC). With DDR5, you get two 40-bit subchannels, 32 of which are used for data transfer. Critically, these subchannels have their own Command/Address (CA) interface, allowing them to operate independently of each other.

In addition, DDR5 doubles the prefetch size to 16N, doubles the number of banks and bank groups, and increases burst length from 8 bytes to 16 bytes. The math here is straightforward enough. With DDR4, you can transfer 64 bits of data over the interface at a burst of 8 bytes, giving you 64 bytes of data and aligning with cache line sizes. Each of the subchannels in DDR5 can transfer 64 bytes of data, as well, with a 32-bit width and burst length of 16 bytes.

It’s pseudo-dual-channel memory on a single DIMM. There are two independent memory operations that can happen each cycle, both of which transfer 64 bytes of data. That is a big reason why even a single DDR5 DIMM (particularly one with a higher data rate) can outpace even a proper dual-channel DDR4 configuration.

The common wisdom about using a single DIMM comes mainly from previous DDR generations, where you can only get that single 64-byte transfer each cycle, necessitating a second DIMM to have two independent operations.

Let me be clear: two DDR5 DIMMs are still better. Instead of two operations per cycle, you can perform four. The main difference is that, for modern CPUs and games, just those two operations give you the vast majority of your performance, and you don’t run into a massive performance bottleneck as you do with just a single operation via DDR4. After all, there are still a lot of DDR4 systems out there.

On the issue of compatibility

The elephant in the room with upgrading to a DDR5 platform with a single DIMM is compatibility. If you get a single DDR5 DIMM now, you should plan to add another in the future. Unfortunately, there aren’t a lot of easy answers when it comes to combining two DIMMs that aren’t in a kit together. It should work, but mixing and matching can lead to stability issues and/or lowered performance.

Generally, combining two DIMMs of the same spec should work. For instance, if you bought this Patriot Viper Venom DDR5-6000 CL30 DIMM to start your new build, and then bought a second one later, it should work. “Should” carries a lot of weight on its shoulders, however. Maybe Patriot sources DRAM from multiple places, or your second DIMM’s timings don’t completely align with your first. That could cause stability or performance issues.

There have been some attempts to get past this hurdle, such as the ROG Certified program with select Asus motherboards, but it’s impossible to know for sure if two separate DIMMs will work together or not without testing. The best you can do is to make sure you buy the same brand of memory, with the same spec, if you add a second DIMM. Make sure to keep your receipt handy in the event you need to return it, as well.

Once you have your second DIMM, make sure to test it first at stock JEDEC speeds/timings (no XMP/EXPO). Run games or applications you normally run, and then use a utility like MemTest64 to check for stability. I’d recommend keeping your PC running in this state for a few days to see if any BSODs, application crashes, or poor performance issues pop up. After that’s done, repeat the process with XMP/EXPO enabled, assuming you’re using matching DIMMs (incompatible XMP/EXPO profiles won’t work together).

Assuming DRAM prices continue at an elevated rate before you upgrade, you may want to consider investing in a dual-channel kit down the line and selling your single DIMM. Even kits can run into compatibility issues, though the likelihood is far, far lower.

M.2-based SSDs have been around for about a decade now in PCs, and have all but replaced the much larger and notably slower 3.5-inch hard drives, and even 2.5-inch drives, both spinners and SSDs. Over that time, we’ve seen these tiny drives increase not only in capacity but also in speed as new flash, controllers, and PCIe generations are released. And with that increase in performance comes increased heat that you need to manage. This is especially true when using the latest-generation PCIe 5.0-based drives, which tend to run hotter than previous-generation drives and are more prone to thermal throttling and performance loss.

Many of these drives already come with heatsinks to help manage thermal output. And so long as it isn’t a simple thin plate, many do the job well enough to either delay or prevent thermal throttling.

However, not all include heatsinks, and if your workflows lean on storage, longer transfers can be significantly slower due to the drive overheating and thermal throttling. The amount of throttling, if any at all (some actually won’t), varies by circumstance. Whether by drive and controller, workload, and even case airflow, these factors affect whether you’ll see thermal throttling and how severe it is. If time is money, this is obviously a bad thing. The longer it takes to read or write the files you need, the longer it takes to finish your work and get to something more pleasurable, or move on to the next task.

You may be thinking: My motherboard has heatsinks for M.2 drives, and of course, if you aren’t using a bargain-basement or business board, you would be right. Those also come in all shapes and sizes (plate-style to massive), with varying cooling capabilities. In general, the more mass a cooler has and the greater its surface area, the better it can cool. There are other variables, including thermal pad efficiency, chassis airflow, and, of course, physical contact, but at a high level, this is the way.

But we wondered if these motherboard heatsinks actually make good contact to whisk away the heat? After seeing seemingly random complaints online in forums and on Reddit over the years, we tested the primary M.2 heatsink from the top PCIe 5.0 M.2 socket on 20 different motherboards to see how many actually make good contact with the included heatsink. And I was honestly a bit surprised at what we found.

What thermal throttling looks like and M.2 contact is so difficult

So what does thermal throttling look like on M.2 drives? It’s a sudden, typically severe, drop in data transfer speeds, appearing as a sharp cliff where blazing-fast speeds plummet to a fraction of the drive’s rated performance, or a saw-tooth pattern where it drops, cools below the critical temperature thresholds (typically by reducing the duty cycle and capping the IO stream and data bandwidth), then jumps back up. Some drives even drop back to PCIe 4.0 to limit bandwidth and reduce thermal throttling.

As you can see from the charts below (which contain throttled and non-throttled results from the same drive), the heatsink-less Transcend 260S 2TB PCIe 5.0 SSD we used for this testing throttled just after the 50-second mark, dropping from just under 4,000 MB/s to around 1,700 MB/s. It then briefly recovered after dropping below its critical temperature threshold (typically between 70 and 85 degrees Celsius) around 90 seconds into the transfer. Several seconds later, it dropped again, and minutes later, it dropped again, this time slowing performance even further to around 600 MB/s, over six times slower than its steady-state performance and much closer to SATA-based SSDs than PCIe 5.0.

That said, it takes a pretty big file/set of files to transfer for over 10 minutes on these speedy drives, so we don’t expect to see this behavior too often during mainstream workflows. Also, how much performance is lost varies by drive and conditions. But this gives you a great idea of just how much performance you can lose.

You’d think that designing a heatsink for cooling hardware the size of a stick of gum would be easy for engineering teams. However, it’s not as cut-and-dry as you may imagine. The reason is that the M.2 standard (governed by the PCI-SIG) lists only maximum Z-heights for single and double-sided drives, leaving board partners to decide, for example, how thick the thermal pad should be. And while thermal pads work better with some compression, too much reduces efficiency, so there is a Goldilocks zone, but one that’s tough to hit consistently, since heights vary by drive.

Below is a handy table that shows the different M.2 SSD form factor standards. Single-sided devices are identified with the “S” in the table, while double-sided drives use the “D,” which shows the z-heights on the top and bottom.

A single-sided drive has components (NAND chips, controller, and DRAM) on only one side of the PCB. These drives can be 1.2-2.0 mm tall on the top side (2.2 to 2.38 mm with the PCB). Double-sided drives range from 1.2-1.5 mm on the top and 0.7-1.35 mm (3.5 to 3.8 mm total thickness). While 0.8 mm on single-sided drives and 0.15 and 0.3 mm for double-sided don’t sound like a lot, they can be the difference between good contact and none at all. So you can see the problem motherboard partners face when trying to consider all the available M.2 drives and their varying component heights.

Results

We picked 20 modern motherboards from AMD with B850 and X870/X870E chipsets, as well as options for Intel's B760, B860, and Z890. They range from budget boards with simple plate-style primary M.2 heatsinks to flagships with massive coolers. While this is only a small cross-section of available motherboards, it gives us a general idea of how good the contact is across brands at various price points, and whether those variables even matter.

We test the contact by removing the primary M.2 heatsink from the motherboard and taking off any protective plastic film. We then install the drive into the M.2 socket, ensuring the motherboard secures it properly with its default latching mechanism. After that, we reinstall the heatsink, ensuring it’s also properly secured. The process isn’t any different from how you would install yours, though I personally press down a bit on the heatsink (on all of my builds).

Earlier, I mentioned I was surprised at the results of our contact tests, and here’s why. Of our 20 tested motherboards, only six made good contact across the ICs on the PCB, and what we’d consider adequate compression across the length of the drive we used for testing (a double-sided 2TB Crucial T705 that’s 3.8mm thick). Five other boards had questionable contact with very light, but complete compression across the drive. Finally, nine boards didn’t make good contact, only touching the controller (arguably the most important part to prevent throttling), and not everything, be it the top or the bottom. See the pictures from each board below.ALBM (40x - board contact images)

Among the brands, MSI had the worst track record across this selection of boards, with only two of six making good contact (Z890 Tomahawk II and X870E Godlike X Edition). The rest had issues with complete coverage, only touching the NAND or the Controller.

Gigabyte had only one of its three tested boards, the Z890 Aorus Elite Duo X, make complete contact on both sides of our double-sided M.2 module, in part because of the M.2 EZ-Flex technology, which offers a flexible base to improve contact between the heatsink and SSD. The former flagship, the X870E Aorus Xtreme AI Top, also uses double-sided pads. Still, it doesn’t utilize the M.2 EZ-Flex technology, and so it made contact only on the top, and there only with the controller.

ASRock had the most tested boards (seven), and four of those had adequate contact. This includes the new X870E Taichi White, the X870 Livemixer and Taichi Creator, and the Z890 Taichi Lite. The B860I Lightning covered only the controller, while the B860 Challenger made contact with all the bits, but with barely noticeable compression.

We tested four Asus boards, and three of those were good, though all had what we’d consider light compression on our test drive. But any contact is better than none or partial. The B850 Creator Wifi was the sole board found to be insufficient, covering only the controller on top and one of the NAND chips on the bottom of our double-sided drive.

From our limited testing, the primary heatsinks on most motherboards don’t make good contact. It was really only a couple that I looked at and said, "Yep, they’re good." It’s inconsistent across brands, and even price points don’t seem to matter, as we’ve seen expensive motherboards fail to make complete contact while inexpensive ones do. Granted, this is a small sample size. If we tested many more boards, a clearer pattern might emerge. But for now, our results point to a disappointingly inconsistent answer to the question of whether motherboard M.2 heatsinks actually cool your SSD as they should.

Gigabyte boards using the company’s EZ-Flex technology look promising for double-sided drives, but that doesn’t leave me much faith in the top and single-sided drives. As noted earlier, this isn’t a specific shortcoming per se, but rather a problem of z-height variability on the drives themselves, which makes it difficult for companies to consistently achieve good contact. A simple answer would be to use a thicker pad and perhaps softer pads to get compression without warping the PCB. But if it were actually that easy, I’m sure the motherboard vendors would have figured this out already. Right?

Conclusion

So what does all this mean? Well, that depends on who you are, or better, how you use your PC. The reality is that most users won’t be affected by thermal throttling very often in the first place. If you’re primarily a gamer, chances are installation times are limited by your internet connection. Game loads are a mix of large and smaller files, many (if not most) of which don’t take more than a minute to load anyway. At that point, depending on the drive, performance has settled to a steady state and is still using DRAM cache (where applicable). Granted, drive throttling depends on multiple factors, and typically only the fastest PCIe 4.0 and PCIe 5.0 drives will throttle.

But if you frequently transfer massive file pools to your M.2 drive, or you're running heavy AI or database workloads, you want to look for two things from the start. First, make sure your drive has a cooling solution on the bottom, in case you have a double-sided drive. Second, but most obvious, is to look for good contact on the heatsink. If you find you don’t have it and absolutely need it, one option is to buy thicker thermal pads with the same or higher thermal conductivity. Something like Thermal Grizzly Minus Pad 8 will do, and it’s a cheap fix with prices ranging from $6.99 to $12.99 for the varying thicknesses (0.5 to 1.5mm). Arctic TP-3 also works well. Another option is to buy a third-party M.2 heatsink (here’s a great article reviewing 30 of them) and remove the cooler that is part of the motherboard.

We certainly expected some variation between boards, but didn’t expect to see so many primary M.2 heatsinks failing to make sufficient contact with our test SSD. Fortunately, for most gamers and mainstream users, it probably won’t matter. But if you regularly move terabytes of data and rely on sustained storage performance on PCIe 4.0 and particularly PCIe 5.0-based drives, it’s worth taking a closer look at your motherboard’s M.2 cooling, or buy one that includes a cooler and use it.

Either way, good airflow inside your case also helps, so keep that in mind, too. But until motherboard vendors find a better way to account for varying drive heights, checking for good contact or spending a few dollars on a thicker thermal pad could mean the difference between getting the performance you bought and leaving it on the table.

The state of PlayStation 5 emulation has been rapidly evolving, partially in response to Grand Theft Auto 6's release later this year. The latest milestone is the first 3D games being playable at very respectable framerates of around 30 frames per second.

The two emulators at the forefront of all this are KytyPS5 and SharpEmu, the former of which is intensely focused on expanding compatibility. KytyPS5 was already able to boot 3D titles and go until their loading screens, with at least two smaller games actually rendering graphics. Now, the same emulator can run two 3D games at around 30 FPS, though there are some glitches.

The first game is XIII, the 2020 remake of the 2003 classic, and it's "playable" at up to 30 FPS with real-time gameplay that accepts player input. We put playable in quotation marks because there are very obvious visual glitches that manifest in the environment not rendering correctly. The textures seem to be broken in multiple scenes, though they don't entirely kill the immersion. XIII is a relatively lightweight game but its cell-shaded aesthetic might be adding to emulation complexity.

The same person who tested XIII also tested Teenage Mutant Ninja Turtles: Wrath of the Mutants and managed to run it at just under 25 FPS with real-time gameplay. The game crashes on the first launch, but once initialized, it's stable and does not seem to have any bugs or glitches like XIII. The framerate looks visibly choppy but is undeniably impressive, on a technical level. Kyty can run other 3D PS5 games as well, but not nearly at this level of performance.

KytyPS5 is advancing at a faster pace than SharpEmu, and that's true for the most part, but not out of stagnation. The team behind SharpEmu is busy tackling a different challenge: accuracy and infrastructure setup rather than game-specific compatibility, per its GitHub repo. In other words, it means fixing low-level issues that are preventing games like Astro Bot from currently reaching the gameplay state.

Both emulators are now part of an unexpected emulation race. With GTA 6 just a few months away and GTA 5 already booting in Kyty, it clearly has the better support for now, and its demos are very promising. SharpEmu's work will undoubtedly help the emulation scene at large, along with RPCSX and other independent developers. The craziest part is that you can try all of this at home for free, and just by doing that you're already contributing to the scene.

AMD officially launched its cheapest RDNA 4 graphics card, the Radeon RX 9050, a few days ago, and we already have some performance numbers for it. Preliminary testing from Japanese outlet GDM puts the GPU up against its closest Nvidia rival, the RTX 5050, in a matchup that sees the AMD offering lose by a big margin. The RX 9050 is fine on its own, especially if you're limited to 1080p gaming, but in the head-to-head it leaves a lot to be desired based on its roughly 30% slower framerates averaged across various titles.

The test bench consisted of a Ryzen 7 9800X3D and specifically the ASRock Challenger variant of the 9050, alongside the Gigabyte Windforce OC variant of the RTX 5050. Starting with synthetic benchmarks, the Red Team's GPU is almost 20% slower in the 3DMark suite. The biggest difference lies in Port Royal, where the RTX 5050 scores 6,181 points but the RX 9050 only manages 4,531 points. Time Spy sees the smallest delta, where both cards are separated by about 500 points.

Moving onto gaming, the testing was conducted across multiple resolutions, so we've chosen to show the most representative results possible. When talking about esports titles such as Apex Legends and Rainbow Six Siege, the RX 9050 holds its ground well, especially as you scale up the resolution. At 4K Ultra+ settings, both GPUs actually match at 64 FPS. The biggest difference was 20%, reported at 1440p medium, where the RTX 5050 pushed 150 FPS while the RX 9050 could only manage 125 FPS.

The rest of the games show a more underwhelming result for the RX 9050, with DOOM: The Dark Ages acting as an outlier where both GPUs take turns destroying the other. The game has multi-frame gen support at up to 6x for the Nvidia card, while the FSR frame gen is limited to just 2x. Regardless, the RX 9050 wins at higher resolutions in all settings due. As mentioned, however, this is the only test where the 9050 seemed to beat the 5050.

The remaining titles show rather boring numbers where the RX 9050 loses every single time, no matter the resolution or preset. It comes the closest in Final Fantasy XIV at 1080p, where the internal benchmark separates the two GPUs by 23%, whereas the biggest difference lies in Onimusha, where the RTX 5050 is almost twice as fast. Across these games, on average, the RX 9050 is 31% slower at 1080p, 34% slower at 1440p, and 42% slower at 4K.

The RX 9050 scores a win in power consumption, drawing about 8W less when idling and about 35W less under heavy load compared to the RTX 5050. The card seems to run cool and quiet, and can be manufactured to be rather small, making it ideal for SFF builds. Overall, it's an okay experience when it comes to gaming, performing amicably in a vacuum, but disappointing against competition. Thankfully, the 4GB variant of the RX 9050 seems to be limited to OEMs. As always, these are preliminary testing results from one outlet, so take them with the customary grain of salt.

The best RAM on the market became even better with the introduction of AMD's EXPO ULL technology, at least for AMD users. Recognizing that not all users have access to EXPO ULL-compatible kits, MSI has stepped up by introducing a new feature called High-Efficiency Mode, which offers comparable optimizations and performance improvements for those who do not own one of the new EXPO ULL memory kits.

AMD EXPO ULL memory kits are similar to standard AMD EXPO memory kits. What really sets them apart is that the former come with specially optimized memory sub-timings that lead to a noticeable reduction in memory latency. The optimizations are done at the factory. MSI's High-Efficiency Mode performs similar optimizations on regular memory kits on AMD motherboards.

Even though machine tuning has improved over the years, it is not a magical formula that works for every single system since each one is unique; The level of optimization will differ with different hardware configurations, and you also have to take into consideration silicon quality. Some samples are just better than others, so you should not expect High-Efficiency Mode to magically match the same optimizations as factory-binned EXPO ULL memory kits. High-Efficiency Mode is essentially the motherboard doing the tuning for you, and as a result, it could introduce system instability similar to manual tuning.

MSI High-Efficiency Mode Benchmarks

MSI’s High-Efficiency Mode is available with four different presets: Tightest, Tighter, Balance, and Relax. Each preset dictates the level of aggressiveness you want the motherboard to use to fine-tune the memory sub-timings for your specific memory kit. There is no one-size-fits-all, so MSI encourages users to experiment with different presets to find the one that is most suited for their hardware.

MSI compared the Trident Z5 Neo DDR5-6000 C30 32GB (F5-6000J3038F16GX2-TZ5N) with its EXPO ULL counterpart, the Trident Z5 NeoX RGB DDR5-6000 C32 32GB (F5-6000A3038F16GX2-TZ5NXRK), to demonstrate the effectiveness of High-Efficiency Mode. On the tightest setting, the Trident Z5 Neo exhibited a 9.8% reduction in memory latency, falling within a hairline of the Trident Z5 NeoX. The other takeaway is that since EXPO ULL memory kits already come with optimized memory sub-timings, enabling High-Efficiency Mode does not offer tangible improvements.

Whether users benefit from improved memory latency depends significantly on the specific workloads they run. For instance, in latency-sensitive workloads such as large-scale databases or compiling complex code, a lower memory latency can lead to substantial improvements. On the other hand, in scenarios like video editing or 3D rendering, memory bandwidth is more important.

Before the memory shortage, the Trident Z5 Neo DDR5-6000 C30 32GB sold for just $119.99. Since then, the same kit now sells for more than 5X its original MSRP. To rub salt in the wound, the Trident Z5 NeoX RGB DDR5-6000 C32 32GB debuts with an additional 4.1% premium on top of the already-inflated price.

While we continue to live in a world with supply shortages and sky-high prices, we'll take anything that can improve performance. If a feature in the motherboard’s BIOS can close the performance gap between standard and premium EXPO ULL memory kits, we are all for it.

Mechanical pressure serves as a better system to design computers around than natural buoyancy, but a new experiment from der8bauer is attempting to challenge that notion. The legendary modder recently built a chimney to exploit the "stack effect," which uses temperature differences to catalyze natural convection to the point where it becomes effective again. As a result, the CPU in his test bench saw temperatures drop by 19 degrees Celsius without any fans.

The video above explains the concept of the stack effect pertaining to its foundation, natural convection, in great detail. Also known as the chimney effect, it relies on differences in indoor-to-outdoor air density, which are dictated by differences in temperature and humidity. The bottom of the chimney becomes a low-pressure zone, sucking in cold air that escapes through the low-pressure exit at the top.

In the experiment, der8auer uses a fog machine to show how a radiator can't "pull" air without fans attached to it; the hot air dissipating from the other side is forced to fall back on natural convection. The test bench was water-cooled and consisted of an AMD Ryzen 7 9800X3D, so he added a temperature probe to the fittings to monitor the water temp as well. The experiment then begins with the first 3D-printed chimney that's 10cm tall — it barely works, but temps already start to drop by 0.5 degrees.

At this point, the water was at 61°C and der8auer added another 20cm chimney atop the previous one, making the enclosure 30cm tall in total. This made the temps drop by another 5 degrees over a 30-minute stabilization period. The fog machine didn't really show any difference in the airflow, however. Now, it was time for the big boy: an 80cm tall chimney made up of 4x 20cm parts, bringing the total height to 110cm.

Right away, temperatures began dropping below 55°C before the modder could even set up his camera for the ultrawide framing this setup warranted. Just five minutes later, the water had hit 50°C, but the visual demonstration really sealed the deal. Turning on the fog machine underneath the radiator showed air being pulled through the chimney as if there were fans facilitating airflow on top.

The CPU temperatures had peaked at 90°C previously, but the "big tower" had now brought them down to just 71°C, as reported by HWiNFO. The experiment was a raging success. The video ends with der8auer actually tying the stack effect back to how we use fans in modern PCs to synthesize air pressure, since they achieve the same goal — a pressure differential — just more reasonably. So, unless you want to redefine what a tower PC means, sticking to regular, boring old fans is enough.

A Qualcomm exec suffered from one of the most disastrous tech demos we’ve ever seen live on stage at Computex 2026 this summer. In what should have been a wow moment during a press event in Taipei, Qualcomm hardware partner NEURA Robotics’ 4NE-1 humanoid robot quickly shifted gears from being a technical tour de force to a crashing mechanical shambles.

Robot powered by Qualcomm’s new AI chip dies mid-presentation from r/singularity

We see that the 4NE-1 humanoid robot is powered by Qualcomm’s Dragonwing IQ10 robotics reference design (RRD), claimed to be capable of 700 TOPS. But even before the robot’s spectacular malfunction, it didn’t look particularly healthy or nimble. 4NE-1’s slow shambling walking style radiated strong Two Soups vibes.

As the robot eventually hobbled close enough to the smart-suited presenter, the on-stage human picked up a Qualcomm Dragonwing IQ10 RRD from the robotically delivered platter and proudly showed it off to the attending crowd. As the applause and whoops subsided, the robot turned to face the crowd, and the presenter rolled on with his spiel.

Seconds into his script, the exec spun away to the side as the 4NE-1 humanoid robot very suddenly and noisily collapsed into a mechanoid mess. After resting in its terminal backbend for a second, one robot hand raised momentarily to make a futile gesture. Thankfully, the glass tray that had carried the Dragonwing IQ10 box onto the stage didn’t shatter.

Stage hands seemed well-prepared

While the overall feeling from watching the video is one of shock from the ambling robot’s sudden noisy collapse, many on social media have commented on how unruffled and well-prepared the stagehands seemed to be. The silent and swift action of the black-clothed helpers, first cloaking the dead robot with purple silks, then the trio carrying it away, exits stage left, making it look like this catastrophe wasn’t such a surprise to some.

As the robotic remains were eventually removed through the side doors, we hear the brave speaker who carried on regardless come to the end of his polished presentation. The crowd politely and quite loudly claps - but is most of the applause for the speech, or for the unflappable stagehands who have efficiently extracted the heap that was the 4NE-1?

This late-emerging clip from Computex 2026 rivals the Windows 98 USB plug-and-play scanner crash during Bill Gates’ presentation at Comdex. That infamous software crash event may well have prompted the creation of the USB Cart of Death.

Keychron, which is known for its mechanical keyboards, just launched a wireless trackball mouse designed to comfortably sit underneath your space bar, complete with six programmable buttons. The Nape Pro wireless trackball mouse is now available on Amazon for $89.99. Although it may look pricey, with comparable ergonomic trackball mice often priced significantly lower, its unique rectangular design makes it the perfect companion for programmers, writers, and those who primarily use the keyboard for productivity. The placement means you don’t have to lift your hands from the keyboard to move the cursor, although it will get in the way if you prefer using a wrist rest.

• Get the Keychron Nape Pro wireless trackball mouse on Amazon.

The keyboard maker revealed the quirky trackball mouse earlier this year at CES, and it’s finally available for those who are interested. It’s wireless, sports six customizable buttons and a control dial, so you can also use it as a macro pad that you can place to the left or right of your keyboard or drawing tablet (or even center, if you have a split keyboard) and pair it with one of the best gaming mice for regular use. But what makes the Nape Pro more useful and powerful is the customizability that Keychron offers. You can change the functions of each button and the dial on the trackball mouse to exactly match what you need. It also has up to seven layers, so you can change what each button does based on what you need.

There are other trackball mice available on the market, like the Elecom Huge Plus with its 52mm ball and 10 programmable buttons (by comparison, the Nape Pro only has a 25mm ball), but they’re mostly designed to replace your mouse with their ergonomic designs. The Keychron trackball, on the other hand, feels like it’s there to complement your current ergonomic mouse and not replace it entirely.

This trackball mouse is another unique product from Keychron, which is known for making one of the best wireless and best budget mechanical keyboards. The keyboard company also makes different types of mice for basic use, productivity, and gaming, but it seems that it hasn’t hit the home run yet on these models. Perhaps the Nape Pro, which is like a hybrid macro pad and trackball mouse, would help elevate its mice to the same level as some of its mechanical keyboards, like the Keychron K3 Ultra.

An intrepid TechTuber has tested a trio of passive mini PCs from the Subway sandwich chain to check if they can be repurposed for gaming fun. In a recent video, Garkus indicates that the three Intel Skylake-powered mini PCs that had been displaying sandwich menus above the serving counters for a decade but were saved from scrap/landfill, alongside a matching set of LG digital signage TVs. Spoiler: they are too puny for mainstream AAA gaming in 2026, even after doubling the RAM installed.

Before getting on with the digital signage-to-gaming conversion, Garkus investigated the hardware in hand. Labeling indicated that the three slim mini PCs were all Advantech DS-081 models (official PDF link). Pondering over that data sheet, we see that the variant with the Intel Core i3 6100U, as these were, carries the full designation of DS-081GB-U21A1E.

The processor is now both long in the tooth and low powered, so immediately we know this 2C/4T @ 2.3 GHz CPU, configured to suck between 7.5W and 15W, won’t be ideal for modern AAA titles. Moreover, the iGPU is the Intel HD Graphics 520 with 24 EUs and clocks up to just 1.00 GHz, sharing the DDR4 system RAM.

A DS-081GB-U2A1E is quite expandable for such a small, low-powered set-it-and-forget-it unit. It has twin HDMI 1.4, twin Ethernet, four USB 3, audio in/out, and an RS-232 serial port accessible from the outside. Inside, users can configure the machine via twin DDR4-2133 SODIMM slots (up to 32GB total), a SATA III HDD/SSD, and an mSATA port that looked like it was an M.2 2242 slot in the video. This passive machine is designed to run signage 24/7 in environments with 0 ~ 40° C (32 ~ 104 ° F) ambient temperatures.

Setup and gaming

These systems were found to actually come with just 4GB of RAM (one slot used) and with a 64GB SATA SSD installed. They booted to Windows and went straight to kiosk mode, displaying the Subway sandwich menu. We saw an extra 4GB DDR4 stick added to bring the test system(s) up to 8GB RAM in total.

After a bit of OS wrangling, Garkus decided to set up the salvaged trio of passive mini PCs as follows. One kept Windows 10, another got Bazzite Linux (because SteamOS balked at the SATA-only storage), then another went Hackintosh with macOS Monterey installed.

Gaming tests began with a very light test. The system ran Peggle, and this 2D puzzler posed no problems. After this modest victory, Garkus ambitiously leapt straight to GTA V. This legendary but now older title could only reach a frame rate of about 15 fps. But it was found to have defaulted to high settings, took ages to get ready to run on Bazzite, then crashed on exit.

Probably not following best benchmarking practice, the tech tinkerer appears to have decided to test Mario Kart Wii emulation performance while GTA V was still compiling shaders… Later, a test run in Minecraft delivered a wildly inconsistent but roughly 25 fps performance. As is now established as the Garkus testing MO, resolution, quality settings, and so on weren’t shared.

To conclude the gaming part of the video, the TechTuber suggests that these ex-kiosk machines are probably best suited to emulating older consoles up to the PS2 and original Xbox era. We think that for PS2 emulation, you will still need to restrict yourself to lighter titles and reduced settings for smooth action.

In the 3D printing community, there’s a common saying: buying a 3D printer is easy—learning modeling, mesh repair, and slicer settings is the real challenge.

While AI-powered 3D generation has made it possible to create detailed models in minutes, turning those models into successful prints still requires significant technical work. From mesh repair and model splitting to print optimization and multi-color workflow management, many AI-generated models never make it beyond the screen.

Hi3D was built to close that gap between AI creation and physical manufacturing. Over the past year, the company has expanded beyond AI model generation, developing an end-to-end workflow designed specifically for 3D printing.

Today, Hi3D has established partnerships across the digital fabrication ecosystem, including Creality, MakerWorld within the Bambu Lab ecosystem, and xTool. These collaborations enable deeper integrations for printable model generation, AMS multi-color workflows, enhanced 3MF output, and broader digital manufacturing applications.

With its anniversary release, Hi3D takes another step forward. Automated part separation, multi-color optimization, color cleanup, material-saving algorithms, intelligent model orientation, and print parameter generation are now unified into a single AI-driven workflow.

The result is simple: tasks that once required multiple software tools and hours of manual work can now be completed automatically—helping creators move from image to printable object faster than ever before.

Hours to 2 Minutes: Auto Character Split with Built-In Print-Ready Tolerances

For makers printing large models—or working with smaller build volumes such as the A1 mini—model splitting is often one of the most time-consuming steps. Traditional workflows require manually cutting meshes, creating connection structures, and adjusting tolerances, often resulting in assembly issues after printing.

Hi3D’s Auto Character Split automates the entire process:

1. Intelligent Topology Recognition – Automatically identifies heads, torsos, limbs, and other structural components, generating optimized printable segments.
2. Watertight Mesh Generation – Every separated part is exported as a closed, watertight mesh ready for slicing and printing.
3. One-Click Joint Creation – Users can instantly add snap-fit connectors, mortise-and-tenon structures, or articulated ball joints for movable figures.
4. AI-Optimized Assembly Tolerances – Mechanical clearances are automatically calibrated for FDM printing, enabling reliable assembly directly off the build plate with minimal post-processing.

Tasks that previously required hours of manual modeling and adjustment can now be completed in just a few minutes.

Deep Integration with the Bambu/AMS Ecosystem: From AI Model to Print-Ready 3MF

Multi-color printing often requires extensive manual color painting and parameter adjustments, especially for complex AI-generated models. Color data can be lost during export, and preparing a print-ready file typically involves multiple software steps.

Hi3D streamlines this process through deep integration with the Bambu Lab ecosystem, featuring an official filament library, automatic color mapping, and enhanced 3MF generation.

Once a model is created, Hi3D automatically maps on-screen colors to official Bambu Lab filament profiles and exports an optimized 3MF file containing print settings such as temperatures, layer heights, infill density, wall parameters, and support configurations.

Instead of manually preparing files in a slicer, users can send the generated 3MF directly to Bambu Studio or OrcaSlicer and start printing immediately.

Reduce Multi-Color Waste by Up to 50% with AI Color Cleanup

For users of Bambu AMS and other multi-material systems, excessive filament purging remains one of the biggest challenges in multi-color printing. AI-generated textures often contain tiny color fragments and gradient noise, triggering unnecessary filament swaps that increase print time and material waste.

Hi3D addresses this with its Color Cleanup algorithm:

• Noise-Aware Color Merging – Automatically detects and removes insignificant color fragments generated by AI textures.
• Reduced Filament Swaps – Minimizes unnecessary color changes during slicing.
• Lower Cost, Faster Prints – Reduces purge waste by up to 50% while improving print efficiency by 30–50%.

Smart Build Plate Layout for Higher Print Success Rates

Model orientation is often the deciding factor in print quality and reliability. Hi3D’s Smart Build Plate Layout system automatically analyzes geometry, center of gravity, and support requirements to optimize model placement.

• Surface-First Mode – Prioritizes visible surfaces to reduce support marks and post-processing.
• Eco-Support Mode – Minimizes support usage while maximizing bed adhesion and print stability.

By automating decisions that traditionally rely on maker experience, Hi3D helps users achieve better print quality with less trial and error.

Bridging the Gap: From Beginner-Friendly Creation to Advanced Manufacturing

Beyond advanced tools for model splitting, multi-color optimization, and print preparation, Hi3D also lowers the barrier to entry through its Maker Templates. Users can upload a photo to generate printable figurines, pet models, or custom keycaps that are automatically optimized for 3D printing.

With its anniversary release, Hi3D is expanding beyond AI model generation into a complete AI-powered workflow built specifically for physical manufacturing. By combining AI creation, print optimization, and hardware-aware automation in a single platform, Hi3D helps creators move from idea to finished object with significantly less manual work.

As AI 3D technology continues to mature, the industry is shifting from simply generating models to generating manufacturing-ready models. Hi3D’s latest update represents another step toward that future, making 3D printing more accessible for beginners while providing greater efficiency for experienced makers.

Ready to experience a smoother workflow from AI-generated models to successful 3D prints? Visit Hi3D.ai and see how AI-powered creation, optimization, and printing come together in a single platform.

New users can receive 300 free Hi3D credits through the link below and experience the complete AI-to-3D-print workflow for themselves—from concept generation to printable 3MF files.

Get started here：Hi3D.ai

Data centers on land are facing increasing opposition and having a hard time getting off the ground — from power connection issues that can take months or years to resolve, to neighborhood concerns about noise and air pollution, as well as their impact on the local water supply. One startup called Atomarine wants to solve this by building nuclear-powered data centers on barges and deploying them at sea.

There have already been various proposals to put data centers out at sea (or even submerged) from established names and startups. We’ve seen conventional examples from companies like Samsung Heavy Industries and Japanese shipping company MOL who to put the servers on dedicated ships and are powered by liquefied natural gas (LNG). There are also more innovative solutions from startups that want to put them in the bases of ocean-based wind turbines or in wave energy converters.

Atomarine differs by building data centers as floating barges, similar to floating oil platforms, which can be deployed anywhere — even in international waters. This should help cut down on the permitting process, and it doesn’t have to worry about disturbing neighbors. The electricity needed to run the infrastructure is then delivered by a power ship moored alongside the barge supplied by LNG ships. Once small modular nuclear reactors (SMRs) become commercially available and certified for shipboard use, operators can then swap out the conventionally powered electricity suppliers with a nuclear one relatively quickly. And because these data center barges are modular in nature, it would be relatively easy to upgrade and scale the floating data center.

While this project sounds promising, building a megastructure like this comes with several challenges. The biggest one is that the ocean is massive and unpredictable, so these barges must be engineered to face extreme weather conditions, making them quite expensive to deploy. It must also be connected to high-speed internet (unless the operators plan to ship tons of drives daily), so they’ll have to lay undersea cables, as well. Furthermore, data servers are particularly sensitive equipment, so they must be upgraded to ensure that they can withstand the continuous rolling motion and the salty environment of the sea. There’s also the question of an SMR’s viability in shipborne use, although the U.S. Navy already has a good track record of running nuclear reactors aboard massive vessels.

The mounting opposition against data centers, both by the general public and politicians, is making it harder and more time-consuming to build new projects across the U.S. While an ocean-based data center like this is likely going to be significantly more expensive and technically challenging than land-based developments, this might become the fastest option in the future if the idea proves to be viable.

Microsoft released Windows NT 4.0 to manufacturing partners on July 31, 1996. Codename Cairo marked an important milestone in the history of Microsoft’s original server OS and would far outlive Microsoft’s original plans as enthusiasts and administrators clung to it, as older readers will be aware. Headlining features of NT 4.0, which made it a winner, include the melding of the intuitive new Windows 95 UI into the fully 32-bit enterprise OS. It was also notable for being the last version of NT to support Alpha, MIPS, or PowerPC CPU architectures.

Historical Windows NT timeline:

• Windows NT Server 3.1 – in 1993, the first version of Windows NT also introduced NTFS
• Windows NT Server 3.5 – in 1994, this update provided integrated support for Winsock and TCP/IP
• Windows NT Server 3.51 - client/server support added in 1995
• Windows NT 4.0 – in 1996, NT got the Windows 95 UI and the familiar My Computer, My Documents, and so on
• Windows 2000 Server – the 5^th NT release started a new naming scheme, introduced Active Directory, plus NTFS 3.0 with file system encryption
• Followed by the more modern Server releases…

After the initial Windows NT 4.0 release, Microsoft followed up with a version for embedded systems and its Terminal Server edition.

The Windows NT line was critical to Microsoft as it led the charge against dominant Unix server software ecosystems. Its first public release was in 1993, with version 3.1, but NT 4.0 coupled the underlying data server and personal workstation tooling with Win95 UI elements such as the Start Menu, Taskbar, Task Manager, and so on. It would also support new components like the cryptography API, DCOM, TAPI 2.0, and some DirectX (v2) features.

Despite all the new technology under the hood and the frills of the latest UI, Microsoft’s Windows NT 4.0 launched with remarkably low minimum requirements. Would-be users were recommended to install it on a PC with a CPU that ran at 33 MHz or better, had 32MB of RAM, SVGA graphics, and a hard disk with 256 MB capacity. This was in the Pentium / Pentium Pro era. NT 4.0 would become “the server for the masses,” boasted Microsoft on the OS’s 20^th anniversary.

Another reason that NT 4.0 was so important is that it formed the foundation for the Windows XP release (2001), leaving the DOS-based 95, 98/SE, and Me versions of the consumer OS behind as archaic hybrids. In the half-decade between the release of NT 4.0 and XP, Microsoft had a lot of work to do, such as implementing Plug and Play, building out gaming tech, adding WDM drivers, and so on. Thankfully, PCs also grew in muscle, specs, and multimedia capabilities to make the larger and more demanding XP a big hit.

Windows XP landed with a core marketing line that it was “Built on NT technology,” which felt uncomfortable to read if you were from the camp that believed ‘NT’ was short for ‘New Technology.’

It is pretty easy to find an old Cairo release online for retro machine tinkering. Those interested in a more casual poke around in NT 4.0 out of interest, curiosity, or nostalgia will find there are some online installs you can play with via a web browser.

Reuters has named Shanghai Aishengna Electronic Technology Group as the state-owned company producing China's first domestic immersion deep ultraviolet lithography (DUV) scanners, a day after news of the program broke without identifying the manufacturer. Aishengna was established in August 2023 with RMB 7 billion, around $1 billion, in registered capital and is thought to have absorbed engineering teams from Shanghai Yuliangsheng Technology and Shanghai Micro Electronics Equipment.

Aishengna has been named by a single source who declined to be named, and its shareholders, SMEE and Yuliangsheng, didn’t respond to requests for comment. SMIC has been testing a Yuliangsheng immersion tool since September 2025, and first deliveries are slated for SMIC, Hua Hong Semiconductor, and ChangXin Memory Technologies.

Photoresist, coater tracks, and light sources

Tokyo Electron held an 89% share of the global coater/developer market in 2022, per Shared Research's analysis of the company's own disclosures, with its chief executive putting the figure near 90% and at 100% for EUV production. A scanner only exposes the wafer, however. It’s the track that's responsible for applying the resist film, baking it, and developing the pattern after exposure, and it has to be mechanically and thermally matched to the scanner in a single cluster, which is why the two are bought together. Shenyang Kingsemi has reached 28nm-class track capability and is currently targeting 14nm.

JSR, Tokyo Ohka Kogyo, Shin-Etsu, and Fujifilm hold a combined 72.5% of the ArF photoresist market, while Chinese suppliers hold under 1% of ArF immersion resist specifically. Nata Opto-electronic built a 25-ton ArF line, later expanded to 50 tons, passed customer qualification in December 2020, and completed project acceptance in 2024 with little volume to show for it. Xuzhou B&C says its ArF immersion products cover 45nm to 28nm and can stretch to 14nm, and chairman Fu Zhiwei has put mass production of China's core advanced resists five years out.

Cymer, Gigaphoton, and Coherent hold more than 80% of the ArF excimer laser market between them, and Cymer has been an ASML subsidiary since 2013. Beijing RSLaser shipped China's first high-power domestic excimer laser in 2018 under the national Project 02 program and has a 4 kHz 193nm ArF prototype aimed at 90nm and 65nm-class tools, generations behind what 28nm immersion requires.

Carl Zeiss SMT has been ASML's sole projection optics supplier since 1983, and Zeiss SMT revenue grew from €1.2 billion in 2016 to €4.1 billion in 2024. It’s not currently known what, if any, Japanese tooling is inside the Aishengna machines, but excimer sources and precision optics are areas where Chinese substitution is believed to be lacking.

CXMT

CXMT is projected to reach around 350,000 wafer starts per month by the end of 2026, roughly 25,000 short of Micron, up from 40,000 in 2020. DRAM scaling at 1a and 1b-class nodes runs on immersion multipatterning because CXMT has no EUV access, which makes any potential ramp lithography-gated rather than cleanroom-gated. DRAM contract prices rose 93% to 98% quarter on quarter in Q1 2026, and TrendForce projected a further 58% to 63% in Q2, lifting DRAM industry revenue 81% to $97 billion. A domestic immersion source is therefore worth having to CXMT, even at inferior overlay and throughput.

A DUV-only 7nm flow needs roughly 19 spacer-defined multipatterning masks from the front end through the second metal layer, against about 10 for an EUV-based N7+ process, by one published comparison of SMIC's process. SemiAnalysis has put SMIC's 7nm defect density near 0.14, around double TSMC's N5 and N6. ASML CEO Christophe Fouquet told analysts during the company's July earnings call that rising DRAM lithography intensity partly reflects "the increased replacement of multi-patterning with more cost-effective single-exposure EUV." As such, every exposure China adds to compensate for the missing EUV burns scanner hours a thin domestic fleet doesn't have.

The MATCH Act

China fell to about 14% of ASML's sales in Q2 2026 from 33% across 2025, and installed base management, the service and upgrade business, brought in €2.8 billion of ASML's €9.3 billion in second-quarter revenue. H.R. 8170 would ban both the export and the servicing of immersion DUV systems to any destination in China and designate SMIC, Hua Hong, Huawei, CXMT, and YMTC as restricted entities by statute. Former ASML chief executive Peter Wennink has said the company can service most Chinese tools, but not with spare parts of U.S. origin that fall under export control, which is the mechanism that the MATCH Act would widen.

The bill remains in committee after clearing the House Foreign Affairs Committee in April, with a Senate companion filed as S. 4281, and no floor vote yet scheduled. Its 150-day allied-alignment clause would also reach Nikon, which sold 11 ArF immersion systems in FY2024 and none in the first three quarters of FY2025, and which plans to deliver a new immersion prototype to a major chipmaker by 2027. ASML expects about 130 immersion shipments this year and intends to raise immersion capacity 30% in 2027, with a further 30% under investigation for 2028.

As for Chinese providers, SMEE prototyped its SSA600 ArF tool in 2011 and never reached sustained commercial sales, and a late-2023 shareholder claim that the company had developed a 28nm machine was subsequently retracted. SiCarrier showed etch, CVD, PVD, and ALD tools at SEMICON China 2025 without a lithography system, and a December 2025 government contract reported as a lithography award turned out to cover a KrF tool at 110nm. We’ve previously assessed that China’s toolmakers are more than a decade behind the market leaders.

The AI Futures Project's June forecast puts a commercially viable domestic 7nm-capable immersion scanner between 2032 and 2038, with a median of 2035, and claims ASML holds 98.7% of the immersion market today. Five machines in 2026 would be under 4% of ASML's annual immersion output, and each would still need a coater track, a qualified ArF immersion resist, and an excimer source to print a single wafer; China leads in none of those three.

Amazon has several internal reports that show how AI is causing the company to overspend on various projects. The Financial Times reports that the cost overruns reached $1.8 million, and that is just for one project. These mistakes used to be “trivially cheap,” but AI models made them “catastrophically expensive,” especially as token spending drastically increased with the deployment of AI agents.

The biggest blunder, so far, is the $1.8-million bill that came from a failed Claude Sonnet AI deployment, which was supposed to match author details with listings on Amazon, representing an 860% increase over the allocated budget that was only detected some five months after the issue started happening. Other problems that surfaced include a $541,000 additional cost that came from a project building, ironically, a financial auditing tool, and a $134,000 extra expense for a system designed to reduce delivery times in the company’s logistics network.

“As with any new technology, we’re experimenting, learning and improving how we use it, including how we drive cost efficiencies,” Amazon said in an internal presentation, according to FT. “Cherry-picking small, isolated examples where teams are learning from one another and portraying them as business as usual doesn’t reflect how teams across Amazon are using AI.” And even though overspending more than a million dollars on failed AI projects might seem excessive for the average person, the tech giant’s latest quarterly revenue sits at more than $181 billion, meaning these excess AI expenses don’t even account for 0.1% of what it makes in a month.

This is not the first time that AI-related issues have cropped up in Amazon’s workflow. Earlier this year, AWS reported several outages that were driven by AI coding bot blunders, but the company fixed this by limiting the access of AI agents instead of giving them the same permissions as the senior engineers that they’re tied to. It also used to have an internal leaderboard that showed which employees used AI the most, but has since dropped it as spiraling AI costs made them think twice about the policy.

Many tech companies have been pushing their people to use AI, supposedly to increase productivity through tokenmaxxing. However, the Uber CTO said that there is no link between this policy and shipping successful products. And as agents took over and AI providers switched from subscription to per-token models, costs have become so great that companies are using up their annual budgets in a matter of weeks. While this might not be an immediate issue for tech giants like Amazon and Microsoft, it is unsustainable for most other companies out there.

I’ve used thousands of laptops over the years, between testing and trade shows, so it isn’t often that an issue pops up that I haven’t encountered before. But that’s exactly what happened recently while working with Acer’s Swift Go 16 AI (review coming soon). This unassuming mid-range portable packs AMD’s Gorgon Point silicon, alongside a large IPS screen and a roomy 7-inch touchpad – nothing groundbreaking, but a solid, svelte system with a metal shell and an affordable price (at least when it’s on sale).

But pretty quickly, when I started setting it up and photographing it, I noticed that the screen would often go black, briefly, when I tried typing, and I would then get kicked out to the Windows lock screen. Since I was using a local account with no password to type in, this was only a minor annoyance at first. But it kept happening – not every time I tried to use the laptop, but often enough that I pretty quickly decided that the review unit must be faulty. Eventually, I reached out to Acer to explain and show them the problem.

Company engineers thought it might be a software conflict, and suggested I reset the system, which I did, to no avail. The screen was still flashing black and kicking me out to the lock screen. In fact, after some experimenting, I could sometimes make the issue occur when I was barely even touching the touchpad. I discussed it with colleagues, sent them the same video I had sent to Acer, and became convinced it was some kind of strange electrical fault with the touchpad. I eventually got a second review unit of the laptop, but by that time I was onto other priorities, so it sat for a week or so, until I decided to at least bring the original “faulty” laptop back to the office so I could box it up and return it to Acer.

Before I boxed it up to send back to Acer for their evaluation, though, I decided to show another colleague, Tom’s Guide’s lab tester Arif Bacchus, in our New York office. He watched me demonstrate the problem for about ten seconds before casually suggesting, “I think it might be your watch.”

This hadn’t even occurred to me, but as soon as he said it, everything started to fall into place in my mind. I had been wearing my Galaxy Watch 7 this and every time I had the issue, because I wear my watch pretty much whenever it isn’t charging. And my watch band (which Amazon tells me I’ve had since May of last year) has a magnetic clasp on the bottom, which sits a few inches behind my right wrist when I’m wearing it. And as I moved my wrist across the lower-right edge of the laptop, the screen went black for a second, and I was once again kicked back to the Windows lock screen.

The touchpad was never the issue, and the laptop isn’t faulty – although it does have a lid sensor that is triggered by a magnet embedded in the upper-right bezel, which can also be triggered by most other magnets if they get close to the bottom-right of the deck. I was able to duplicate the issue with a fridge magnet, a magnetic Qi 2 accessory, and a borrowed Apple Watch, which also had a band with a magnetic clasp.

While perhaps not the greatest of design choices, this is, to be clear, an issue that probably won’t affect a large portion of people. To run into the problem I had with this laptop specifically, you’d need to have a magnetic watch band and either be left-handed or the odd right-hander like me who also likes wearing their watch on their right wrist.

I wasn’t able to replicate this issue on any of the four other laptops (Dell, Apple, Lenovo, and Framework models) around my desk area. And the issue must be quite rare as, again, I have been wearing this watch band every day for 14 months or so, at CES in Las Vegas and two Computexes in Taiwan, where I put my fingers on dozens of laptops, and have never encountered screens that dim or turn off as my hands land on the keyboard deck.

There are definitely other documented instances of this happening, though. Once I knew what to look for, it was easy to find a few (but not particularly a lot) of discussions about this and related issues, on Reddit, Apple, Dell, and Acer forums, and a Medium article about Chromebooks confusing Apple watches. Some older mentions also note that magnetic bracelets can cause the same issue (somewhat obviously).

Clearly, this isn’t a new problem, but it isn’t well known. It was confusing enough that I was convinced the laptop was faulty and asked for a replacement. If I owned this Acer, it probably would have led me to return it and deal with an RMA process, only to eventually get another laptop that, even more frustratingly, would have the same issue. And yes, the replacement Swift Go 16 AI that Acer sent was also fooled by my watch band.

So what do you do if you have a laptop with a lid sensor that is triggered by your watch band? Your options should be pretty obvious.

You could get a new, non-magnetic band. I do love the convenience and easy removal of my current band, but this is probably the simplest solution.

You could learn to love wearing your watch on your opposite arm. For most people, this might be tough, but I do switch up watch arms now and then when my right wrist gets irritated by the fact that I track nearly every waking and sleeping moment of my life with my smartwatch. And if you aren’t using your PC during most of your waking hours like me, switching your watch to your other arm or taking it off just while working or gaming might be easy enough.

Also, if you just bought a laptop that is triggered by your favorite watch band, and you don’t want to give that up, you could return the laptop for something else.

The good news is that it’s unlikely any other random model you choose will have the same problem. Perhaps this magnetic sensor issue is more common on Chromebooks (which I tend to avoid), but none of the dozens of other laptop models I’ve put my wrists on since May of 2025 have been triggered by my watch strap. So if you’re unlucky enough to be struck by the curious watch strap laptop curse once, it probably won’t happen with the next laptop you choose. Still, it’s always good to check out a laptop in a store, if you can, for this and several other reasons.

Our local AI explorations in 2026 have so far focused on two main platforms: Nvidia’s GB10, as seen in the DGX Spark and Dell Pro Max with GB10, and AMD’s Ryzen AI Max+ 395, aka Strix Halo, as seen in the Corsair AI Workstation 300 and the Ryzen AI Halo. We’ve generally favored GB10 systems for these kinds of local AI development sandboxes. Their solid all-around performance and broad AI software compatibility make them easy to love, even if raw LLM inference throughput isn’t that high.

But Apple’s Mac Studio is another compelling option for local AI trailblazers who want systems with large unified memory pools, powerful GPUs, and high memory bandwidth to enable faster tokens-per-second throughput than either GB10 or Strix Halo can provide. And until someone builds another unified memory SoC with a memory bus as wide as what Apple uses for its Max and Ultra chips, Apple Silicon is, in fact, the only game in town for more memory bandwidth from a chip of this design.

Why focus so much on memory bandwidth for local LLM performance to begin with? To keep it very short, the decode phase of LLM inference is virtually always sequential. Every output token (starting with the first one generated as part of the prefill process) has to be run through every layer in a model in order to generate the next token, and so all the active model weights in a layer have to be streamed to the GPU from its memory as the token makes its way through each one.

Because the amount of computation required for each individual token at each layer is tiny, the speed of the entire decode process basically becomes dependent on how fast those model weights can be streamed in from GPU memory. That makes systems with large memory pools (for holding large models) and high memory bandwidth (for streaming those model weights to the GPU) appealing, and Apple Silicon is the only platform that lets you have both characteristics at a (relatively) reasonable cost.

Apple’s last Mac Studio refresh was in March 2025 and marked the introduction of two versions of the system. The higher-end version uses the M3 Ultra SoC with 819GB/s of memory bandwidth across both the 28-CPU-core, 60-GPU-core mode and the 32-CPU-core, 80-GPU-core model.

The M4 Max version of the Mac Studio encompasses two versions with greater divergence in specs than just core counts. The base M4 Max includes a 14-core CPU (10 performance cores and four efficiency cores) with 410GB/s of memory bandwidth, and it can be upgraded to a 16-core CPU (12 performance cores and four efficiency cores) with 546GB/s of memory bandwidth.

We reviewed both of these systems at launch, but Apple generously lent us another M4 Max with the 16-core CPU, 40-core GPU, and 128GB of memory for LLM-specific tests. At the time, the price of that system was $3,699 or so, close to the DGX Spark’s $3,999 list price.

But as the RAMpocalypse has rolled on, the Mac Studio has become more limited in its configuration options and harder to find in stock. The M4 Max version we tested now tops out at 64GB of RAM, and lead times for that system are over two months out. Regardless, it’s the most comparable system that Apple has for the DGX Spark and GB10 platform more generally, at least back when dollar-for-dollar meant something in this market.

Before we get into performance results, we wanted to dig into the nitty-gritty of the M4 Max’s 40-core GPU, but Apple doesn’t share much (if any) detailed architectural information on its GPUs, including the number of shader ALUs that make up each GPU core, so it’s hard to directly compare the M4 Max to GB10 or the Radeon 8060S in the Ryzen AI Max+ 395.

The Radeon 8060S on board Strix Halo has 40 RDNA 3.5 compute units, each with 64 shader ALUs for a total of 2,560. AMD clocks the 8060S high, at 2900MHz, to achieve its roughly 14.8 TFLOPS of peak FP32 vector math.

Meanwhile, GB10 has 48 Blackwell SMs with 128 shader ALUs each for 6,144 total CUDA cores, and it too clocks relatively high, at 2450MHz in our testing. It offers a whopping theoretical 30 TFLOPS of FP32 vector compute.

Way back in the day when Apple first revealed the M1 GPU, however, the company disclosed that each core encompassed 128 execution units. Assuming that the same organization has carried through to current Apple GPUs, the 40-core M4 Max GPU would have 5,120 execution units or shader ALUs. That provides an idea of the scale of the GPU, at least, though without knowing clock speeds, we’re hesitant to speculate further about peak FLOPS or other theoretical performance measures.

Apple also only provides raw memory bandwidth figures for the M4 Max, but we can do some back-of-the-napkin math to surmise that the chip likely uses LPDDR5X-8533 on a 512-bit bus to achieve its 546 GB/s of rated memory bandwidth, twice as wide as both GB10 and Strix Halo. The lower-end M4 Max likely uses LPDDR5X-6400. In turn, the M3 Ultra likely uses a 768-bit-wide bus with LPDDR5X-8533 across both of its variants.

We covered the design of the Mac Studio in detail in our initial review, but it’s worth a quick tour to re-familiarize yourself with it. The top and sides of the system are largely featureless, save for an inlaid black Apple logo up top. The front panel has two 10Gbps USB Type-C ports and a UHS-II SD card reader.

The Studio’s thermal design uses a clever intake system that draws in air from vents around the system’s circular foot before exhausting it through a vent at the back of the chassis.

The M4 Max Studio we tested has a whopping four Thunderbolt 5 ports on its back panel with support for data rates up to 120Gbps. Although we’re not testing it today, you can enable RDMA over Thunderbolt 5 for low-latency clustering of Mac Studios using utilities like Exo. These ports also support Thunderbolt displays or DisplayPort 2.1 Alt Mode.

This system also has two USB 3 ports running at 5Gbps, 10Gb Ethernet, an HDMI 2.1 port, and a headphone jack, so it’s got all the connectivity you could practically want out of a compact desktop in 2026.

With those basics out of the way, let’s get to testing.

To test LLM inference performance, we once again turn to llama.cpp, which includes native Metal/MLX support on Apple Silicon when built from source. We used the llama-benchy project as our benchmarking harness.

We tested three models of various memory footprints and architectures: Qwen 3.6-35B-A3B, a recent mixture-of-experts model; Gemma 4 12B, a small dense model, and OpenAI’s gpt-oss-120b, a large mixture-of-experts model. We used Unsloth’s four-bit quantizations of these models for our testing.

Out of the gate with Qwen 3.6-35B-A3B, the Mac Studio delivers prompt processing speeds that beat Strix Halo but are still behind GB10, especially with longer contexts.

Flip over to the throughput results, and the M4 Max pulls ahead of both GB10 and Strix Halo, turning in higher tokens-per-second throughput than both those systems at all context depths.

But despite having double the memory bandwidth of GB10 and Strix Halo on paper, the real-world improvement in token throughput on the M4 Max is just 25% on Qwen 3.6-35B-A3B. That’s certainly welcome, but it’s not nearly the speedup you might expect with twice the memory bandwidth on tap.

The dense Gemma 4 12B, on the other hand, really seems to let the Mac Studio’s bandwidth advantage shine. Tokens-per-second throughput scales more linearly with memory bandwidth with this model, and so the Mac Studio delivers a 1.8X increase in throughput over GB10 and a 2.26X increase over Strix Halo.

But prompt processing speeds are only in line with (or even slightly worse than) Strix Halo here, which isn’t a fantastic result for latency if that’s important to your application.

Finally, we’ll look at gpt-oss-120b. Prompt processing again lands between Strix Halo and GB10, and tokens-per-second throughput is far higher than with either of those systems. But the Mac Studio’s tokens-per-second throughput is, on average, 1.5x higher than GB10 and 1.6x higher than Strix Halo, despite its much higher memory bandwidth. Those are still impressive leads, but they show that memory bandwidth is just one component in judging the performance of an inference pipeline.

On the whole, our LLM inference testing shows that the M4 Max GPU can generate many more tokens per second than competing systems with large unified memory pools, but a memory bandwidth specification alone isn’t a good proxy for delivered performance. The actual boost you get from the M4 Max in LLM inference is highly dependent on the architecture of the model you want to run, so real-world benchmarking is still important.

Image generation performance

LLMs aren’t the only AI workload that one might want to run locally. Image and video generation also matter, and the performance of these diffusion models is generally bound by the compute throughput of the underlying GPU.

Running our Flux.2 Klein image generation test on the Mac Studio initially failed due to an apparent lack of GPU support for the FP8 data type that the ComfyUI workflow uses by default.

We were able to modify the ComfyUI workflow to use the base FP16 version of Flux.2 Klein on the Mac Studio, but that initial compatibility issue shows that you might not enjoy as smooth an image or video generation experience on Apple Silicon as you might on GB10 or even Strix Halo.

Compatibility issues aside, the M4 Max GPU requires even more time than the already pokey Radeon 8060S in this image generation test. Nvidia has repeatedly demonstrated the DGX Spark running as an image and video generation companion for Macs in its demos this year, and this result demonstrates why that pairing might make sense.

Image generation performance with the latest M5 GPU and its dedicated Neural Accelerators for matrix math might be better here, but we don’t have an M5-powered system at hand to compare against the M4 Max. Apple does claim that the M5 Max is “up to 3.8x faster” at image generation than the M4 Max, so take heed if this workload is important to you.

General CPU performance

We already gauged the CPU performance of the M4 Max in our initial review, but we wanted to stack it up against Strix Halo and GB10 directly to see how it performs against these popular platforms in the AI space. To establish a CPU performance ballpark for the M4 Max, we fired up the just-released Geekbench 7 and got to it.

In this benchmark, the M4 Max turns in a whopping 27% advantage in single-core performance and a 21% boost in multi-threaded performance versus the Ryzen Max+ 395’s 16-core, 32-thread Zen 5 x86 CPU.

And comparing Arm to Arm, the M4 Max delivers a 39% single-threaded advantage over the Cortex-X925 “big” core on the Nvidia GB10, along with a 22% advantage in multi-threaded work.

Those results are seriously impressive on their own, but Apple has even more advanced CPU cores in its arsenal now on board the M5 series. We’d expect even larger advantages in general use from those chips.

Geekbench is fine for a quick synthetic test, but I wanted to make sure that its results held in a real-world task, so I compiled the CPU-only version of llama.cpp from source across all three of our test systems using the Clang 21 compiler running across all available physical cores.

With all 16 of its CPU cores in the game, the M4 Max finishes this compilation job in about 37 seconds, anywhere from 33% to 37% faster than the Nvidia and AMD competition here. That’s even faster than the M4 Max’s Geekbench multi-threaded performance delta would suggest.

At least going by these high-level tests, Apple’s CPU performance among SoCs with large unified memory pools is best-in-class, and by a wide margin. And again, that’s with the last-gen M4, not the latest M5.

When judging the efficiency of Apple Silicon or any other platform, one might be tempted to just glance at a power meter like a Kill-a-Watt with the system under load and leave it at that, but instantaneous power draw isn’t the right metric when judging the efficiency of a system for a given task.

Task energy (the amount of power consumed over time) is much more informative. A system that needs a lot of power but finishes a task quickly may consume less task energy and is therefore more efficient than one that consumes a moderate amount of power but takes much longer to finish a job.

To judge inference efficiency, we set up a fixed-length workload with gpt-oss-120b using llama.cpp and llama-benchy: first processing a 2048-token prompt against a 32768-token context depth, then generating 1024 output tokens. We chose that context depth to ensure that our test ran long enough to collect useful data. We recorded this data in watt-hours so that it reflects both energy consumed and time to completion.

At least in this synthetic workload, the M4 Max is more efficient than Strix Halo, but the sheer prompt-processing speed of GB10 lets it finish much faster and use less total power than the Mac Studio does, even though it’s outputting fewer tokens per second in the decode stage.

This test once again suggests that fixating on tokens-per-second throughput alone is perhaps not ideal for judging a system’s inference performance. An ideal LLM inference system would have both high prompt processing speeds and high tokens-per-second throughput for the shortest possible inference turn.

We’re curious how Apple’s latest M5 Max GPU would perform on this workload, as the company claims big gains on prefill compared to the M4 Max and has given that chip even higher memory bandwidth than the M4 Max. If that’s true, the combination of fast prefill and high tokens-per-second on decode would likely make the M5 Max competitive with GB10, if not an outright leader here.

We also gauged idle and load noise levels of these systems to see what it’s like to share space with them. For reference, the noise floor in our testing environment is about 32.6 dBA. We measure sound pressure levels at a distance of 18” from these systems to approximate what it’s like to work with them on top of a desk.

The Mac Studio is impressively quiet both at idle and under load. It barely raises the noise level in our testing environment at idle, and under load, its fans are barely perceptible. Practically any other noise you make or hear in your space will be louder. This is superlative performance.

Our time with a 128GB M4 Max Mac Studio demonstrates why these systems have been so popular among local AI trailblazers. For starters, the spec we tested has an incredibly potent 16-core CPU that’s leagues ahead of both Nvidia’s GB10 and AMD’s Ryzen AI Max+ 395 in both single-threaded and multi-threaded performance.

The massive memory bandwidth advantage of the 40-core GPU configuration of the M4 Max versus Strix Halo and GB10—546 GB/s vs 273 GB/s—also translates directly to higher tokens-per-second throughput in local LLM workloads. The M4 Max’s LLM inference performance is by far the highest of any unified memory platform we’ve tested.

But our tests demonstrate that there’s much more to delivered performance than that raw bandwidth figure. Depending on the model you choose, you might see the M4 Max generate as few as 27% more tokens per second or as many as 82% more TPS than an Nvidia GB10 box, at least with the llama.cpp inference engine.

This result emphasizes that you can’t just eyeball memory bandwidth and conclude that twice the bandwidth means twice as many tokens per second for LLM inference. Testing actual workloads remains essential.

And the Mac Studio doesn’t totally wipe the floor with the competition in our tests. For work like image generation, the Nvidia GB10 GPU still holds a large advantage over the M4 Max. Apple claims this workload will perform significantly better on the most recent M5 Max with its latest GPU architecture.

Beyond its impressive raw performance with LLMs and in general processing tasks, the Mac Studio is a master class in industrial design. It looks distinctly classy on a desk, and its cooling design keeps it incredibly quiet. Under load, it’s barely louder than the Nvidia GB10-powered Dell Pro Max and Ryzen AI Halo are at idle. And when the Studio itself is idling, it’s practically silent. This level of performance in such a compact, quiet, and refined chassis is incredibly impressive.

There’s one major asterisk, though: the ongoing RAMpocalypse means that even if you do want to use a Mac Studio as a foundation for your local LLMs, these systems are no longer available in the configuration that we tested.

A Studio with the high-end M4 Max as seen in this review currently tops out at 64GB of RAM for $5299, and the M3 Ultra version tops out at 96GB (with an even higher 819GB/s of memory bandwidth) for the same price. But neither of these configurations are available from stock, and lead times for both are about two months out, meaning that you practically can’t buy a Mac Studio new right now.

If you really want to try out local AI on Apple Silicon with a large memory pool to match, the best current option may be a MacBook Pro with an M5 Max inside, which is still readily available from stock, still allows you to get up to 128GB of RAM, and benefits from Apple’s latest GPU architecture with dedicated Neural Accelerators for matrix math operations.

But depending on your SSD choice, a 128GB M5 Max MacBook Pro with the highest-end 16-core CPU and 40-core GPU is still a $7K to $10K system today. Even in today’s world of rising prices for access to frontier models, that’s a lot of tokens from the cloud – and, almost assuredly, more intelligent ones – than anything you can get from a single 128GB system from any vendor.

But if you’re dead-set on a single Apple Silicon system with the most memory possible, and you want it now in order to ride the local AI wave, a maxed-out M5 Max MacBook Pro is your only ticket at the moment. Given the refinement and flexibility of the Mac Studio as a desktop or server, we can only hope Apple brings that chip to this system, too.

Google was among the first hyperscalers to develop its own custom AI processors about a decade ago and has been steadily ramping their deployment since then. The company seems to be so confident about its TPU v9 due in 2028 that it intends to order 12 – 15 million of such processors, according to a Fubon Research note to clients published by Sean. If the information is correct, Google may not only produce more or a comparable number of AI accelerators than Nvidia, but may also need to use Intel Foundry to meet its goals.

"Based on our checks, Google plans to have 12 – 15 million TPUs in 2028," the paper reads. "Entering 2028, Google’s TPUs will enter the V9 generation with four compute dies, suggesting that their capacity consumption will more than double in 2028 versus 2027."

Fubon estimates that Nvidia supplied 8.2 million data center AI GPUs in 2026 and is on track to increase the number to 12.4 million in 2028. If Fubon is correct about Google's plans to produce 12 – 15 million 9th-generation TPUs in 2028, then the company may produce more, or at least a comparable number of AI accelerators, than Nvidia in 2028.

TSMC is not enough

How the performance of Google's v9 TPUs will stack against Nvidia's Rubin and Rubin Ultra is something that remains to be seen, but the fact that Google intends to use four compute chiplets on these AI accelerators clearly points to the fact that the company bets big on the performance of these processors. Meanwhile, building an AI accelerator with four large compute chiplets is a major engineering effort, which Google seems to have accomplished.

"Although we do not have the detailed allocation yet, we think it is difficult to reach Google’s target with TSMC alone, and Intel's supply is a must by 2028," the paper continues.

Researchers from Fubon are not sure whether Google's allocations at TSMC will be enough to meet the company's demand for 12 – 15 million 9^th Generation TPUs, so they think that Google will have to use Intel Foundry's capacity to meet its volume goals. Over the past few months, we have seen reports claiming that Intel had landed orders to make three million TPUs for Google following months of Google's testing of Intel's advanced packaging technologies. Indeed, if Google wants to make its silicon at Intel Foundry, usage of Intel's advanced packaging services makes great sense. It should be noted that when compute chiplets are developed, they must be developed with their packaging technology in mind, as Intel's EMIB/EMIB-T and TSMC's CoWoS-L are incompatible.

World's largest consumer of AI accelerators

If the information about Google's plans to produce 12 – 15 million TPUs in 2028 is correct (note that the difference between 12 and 15 is 20%, which is huge) and Google will indeed deploy more AI accelerators annually than Nvidia sells to the entire market, it would mark a dramatic shift in the AI hardware landscape. It will not only make Google the world's largest consumer of AI accelerators (as the company will unlikely cease buying Nvidia hardware), it will eventually make Google the owner of the world's most capable AI hardware fleet. Whether or not Google will use its overwhelming AI compute capacity primarily for its own services, or will lend the majority to other is something that remains to be seen.

Meanwhile, for Google's rivals, the milestone will underscore the growing importance of vertically integrated AI infrastructure, where cloud providers design chips tailored to their own software stacks, workloads, and data centers instead of purchasing off-the-shelf GPUs.

Yet, Google's surpassing Nvidia in unit shipments would not necessarily diminish Nvidia's dominant position. AI demand continues to expand so rapidly that both companies could increase deployments simultaneously, but Google will simply grow faster, at least till Nvidia ups production of its AI accelerators with Feynman and Feynman Ultra in 2029 – 2030. After all, Nvidia's AI GPUs are sold out. What Nvidia should worry about is not the volumes of TPUs that Google can deploy, but rather the fact that these processors do rely on a software stack that rivals Nvidia's CUDA, the company's main competitive advantage.

If you were hoping GPU prices would settle down anytime soon, you are in for disappointment. Nvidia’s RTX 5080 and RTX 5090 models from various OEM partners are once again selling well above their launch prices. As per a recent listing noticed by users on Reddit, the Asus ROG Astral RTX 5080 is now priced at $2,099.99 at Best Buy. That's $600 above its official launch MSRP of $1,499.99 and even $100 more than the flagship RTX 5090's launch MSRP of $1,999.

Similarly, pricing for the RTX 5090 has also skyrocketed in recent months. According to a Reddit post, the Asus ROG Astral RTX 5090 is currently listed at $4,329.99 on Amazon, roughly $1,530 above its launch MSRP of $2,799.99. Even the MSI Gaming Trio RTX 5090 has gone up to $4,299.95, a whopping $1,900 more than what it was when it debuted in early 2025.

That said, these hefty prices are primarily limited to premium partner models. Certain mainstream RTX 5080 cards can still be purchased closer to Nvidia's MSRP. For instance, Zotac's RTX 5080 Solid OC is selling for $1,249.99 on Amazon while PNY's RTX 5080 OC is listed at 1,256.99 at Best Buy.

While one cannot ascertain the exact reason behind this price increase, it does take us back to when tech YouTuber der8auer claimed that Nvidia has discontinued its Observed Pricing Program (OPP). This was essentially an incentive scheme that helped board partners to sell certain Nvidia products at or near MSRP. The termination of this program meant that manufacturers such as Asus, MSI, and Gigabyte gained no incentive to keep prices close to Nvidia's suggested retail price. As a result, premium custom cards have become even more expensive, with manufacturers passing higher production costs on to the consumers.

In addition to that, rising DRAM prices thanks to AI-driven demand have led to a massive increase in the cost of GDDR7 memory used in RTX 50-series cards. Nvidia was also said to be prioritizing production of higher-margin products, including the RTX 5080 and AI hardware, which has further tightened supply of certain gaming GPUs.

For potential customers, the latest listings suggest that waiting for premium RTX 50-series cards to return to MSRP may take longer than expected. While Founders Edition models remain the closest option to Nvidia's suggested pricing, they're often low in stock, forcing customers to choose between paying a hefty premium for high-end partner cards or settling for more affordable custom models.

When you build a new PC, there are many things to factor in. I personally like to build rigs that, first, are capable of the tasks that I want them to perform, and secondly, are equipped with components and specs that can afford me some amount of future-proofing. In my household, we operate a trickle-down system, where my son inherits my PC bits and pieces when I upgrade parts, so they can’t be too out of date, or I get complaints.

I use my PCs for video editing, streaming, and various other content creation and productivity tasks, but I also use them for some PC gaming fun. There’s always a pull towards going for the biggest and the best when building a gaming PC, so you can have settings dialed up to the max, with incredibly smooth frame rates on a ridiculously expensive monitor with an insane refresh rate. But unfortunately, I don’t have unlimited funds.

Everyone knows that having a higher-end graphics card, with bigger processors and more VRAM, has a direct impact on how your game runs, but what’s not so clear is how much effect your SSD storage pick has on your game's performance metrics. The short answer is that it’s not as important as your CPU or GPU, but it typically only has a slight effect on your game performance, depending on the game you're playing and whether it’s streaming levels or pre-loading them.

The most important thing to first factor in with an SSD is the capacity. Games have grown in size exponentially over the last decade, with some of the latest titles demanding up to 150GB and more just for the one game. My son's Ark: Survival Evolved game with all the added DLC content fills up a 512GB SSD on its own, so if you have a lot of games that you want ready to play at a moment's notice, then you need a larger capacity SSD to have them all installed. In my gaming PC, I have 6TB of storage, which is ample for me, and because I don’t have the fastest internet connection, I prefer to keep my games installed.

If you have an amazingly fast internet connection with high download speed capabilities and don’t need to worry about any kind of metered connection rates, then this will also affect how much storage you need. If you can download any game you want in 5-10 minutes or less, then capacity isn’t as big a concern. You can just uninstall and reinstall a game whenever you want, provided you aren’t in the danger zone with your SSD endurance metrics. The minimum-sized SSD I’d recommend, though, is a 1 TB drive.

If you’re running a traditional hard disk drive for gaming, you should definitely upgrade. An HDD has an average read speed of 100-150 MB/s, compared to the latest PCIe 5.0 SSDs that have peak read speeds of around 14,500 MB/s. Now, although you don’t need read speeds that fast for gaming, the difference is humongous. A game running on an HDD may take 45 seconds to load a level, compared to just a few seconds for the SSD. Even the oldest SSD technology would be an improvement over your optical disk.

When building or upgrading a gaming PC, SSD manufacturer marketing often pushes massive sequential speeds (like 7,000 MB/s or 14,000 MB/s). However, the real-world impact of read and write speeds on actual gameplay is much more nuanced. The effect that a superfast PCIe 5.0 SSD has on frame rates compared to a PCIe 3.0 SSD is virtually imperceptible, as the frame rate rendering is predominantly handled by your GPU, VRAM, CPU, and system RAM. Your PC will use your SSD to load game assets from storage into the VRAM/RAM, and then mostly sit idle during the rendering of the game while you’re playing it.

If you’re playing a game with a massive open world or large levels, there may be the occasional request for assets (textures, models, shaders, etc.), but the most important spec of your SSD in that scenario will be its IOPS speed, or random read speed. Write speeds typically do not affect active gameplay performance, as playing a game predominantly consists of read operations.

Patching the game, downloading the game, or copying a game file will make use of the SSD's read and write speeds. And if you use background recording programs like SteelSeries GG, Xbox Game Bar, or OBS, that will also make use of the drive speeds, but again, the effect on the actual gameplay is typically very minimal.

So, to answer my initial question, how much SSD storage and speed do you need for pure gaming? Well, you can use anything from PCIe 3.0 to PCIe 5.0; the impact of peak read and write speeds is often negligible if you aren’t playing a Direct Storage-capable title. Capacity is the most important factor, and you should base that on how many games you want to store on your system. If you want to choose your SSD to perform more than gaming, then the speeds start to matter, plus SSD features like DRAM and HMB, but that's another story.

Your choices will also be very much affected by pricing. If you can get a 4TB PCIe 4.0 SSD for the same price as a 2 TB PCIe 5.0 model, the choice is simple. However, we are in one of the toughest periods in recent memory for storage prices, and the usual rules don’t apply. Prices are all over the place, with PCIe 3.0 drives not necessarily cheaper than the more recent PCIe 4.0 and PCIe 5.0 drives. What was $80 a year ago is now $250 for the same product. To give you a small idea of prices and capacities, here are some of the most popular SSD drives with their PCIe generation, capacities, and prices.

PCIe 3.0 M.2 SSDs

PCIe Gen 4.0 M.2 SSDs

PCIe 5.0 M.2 SSDs (Ultra High-End)

After granting about a dozen manufacturing licenses to make various x86 CPUs back in the 1980s, Intel ceased to license both its cores and instruction set architecture (ISA) in a bid not to create rivals. However, in an unusual turn of events, Intel has quietly granted startup RosaicLabs access to its Atom processor technology, reports Reuters. The company was incorporated in May and is led by Lip-Bu Tan's co-investor.

Intel provided Rosaic access to an unknown Atom-class core, which enables the company to build its own custom processors based on x86 general-purpose cores, according to the report. The renowned chipmaker plans to ship Rosaic register-transfer level (RTL) code ​for the Atom processor core, which will let the startup build its custom system-on-chip (SoC) both at Intel Foundry and elsewhere.

The startup is reportedly led by Amarjit Gill, a venture capital investor who partnered with Intel's CEO, Lip-Bu Tan, on multiple occasions in the past. The two invested in such companies as Nuvia and Rivos, which were later acquired by Qualcomm and Meta, respectively.

RosaicLabs does not have a website or a LinkedIn profile, which is common for startups when they operate in stealth mode. The company was incorporated in May and is currently seeking a seed funding round of $10 million, according to a document seen by Reuters.

Since RosaicLabs does not have a website or a LinkedIn profile, it is completely unknown what kind of SoC it plans to develop and which markets it is going to pursue. One could imagine that it is in Intel's interests to license technology to companies that seek to address markets which Intel has no plans to address.

Arguably the biggest question is which Atom-class core Intel licensed to Rosaic. Traditionally, Atom cores were developed for inexpensive low-power devices, applications that Intel ceased to address about a decade ago. Since then, the low-power x86 architecture has been used to build custom SoCs for telecom and adjacent applications, embedded CPUs, efficiency (E) cores for client CPUs, and more recently cloud-optimized Xeon processors. Intel's most advanced low-power x86 cores to date are Crestmont, which powers Xeon 6700E-series CPUs, Skymont, which is used in Core Ultra 2-series CPUs, and Darkmont, which powers Xeon 6+ CPUs.

Skymont and Darkmont feature a 9-wide decode, 8-wide out-of-order engine, and 16-wide retire, which makes them fairly capable cores that wed high performance potential with energy efficiency. Meanwhile, Darkmont is optimized for data center workloads, so it has better branch prediction, improved prefetch, an enhanced vector engine, and higher L2 bandwidth. By contrast, Crestmont features a 6-wide decode and an 8-wide retire, which puts it well behind the newer cores.

If Intel gives Rosaic complete, synthesizable RTL of an Atom-class core, Rosaic could technically modify the core at several levels, including changing cache sizes, reorganizing the pipeline, increasing clocks, and altering power-management logic, just to name a few options. However, this does not automatically mean Rosaic has unrestricted rights to enhance Intel's technology, as the company could provide RTL under various conditions with numerous restrictions. After all, it does not want to create a competitor for itself. Still, we do not know the terms of the license.

Intel granted about a dozen manufacturing licenses to build its 80286 and 80386 CPUs in the 1980s to various chipmakers in a bid to provide chipmakers with second sources for its processors and expand usage of its x86 ISA. However, only AMD got an actual x86 license that allowed it to build x86 CPUs of its own designs.

After disposing of its StrongArm/XScale business to Marvell in 2006, Intel witnessed the smartphone revolution essentially empty-handed as its Atom processors could not compete with highly integrated Arm-based SoCs in handsets. Intel tried to expand the reach of its low-power Atom CPU cores in 2009, so it signed a memorandum of understanding with TSMC and planned to port its Atom cores to a TSMC node and enable TSMC clients to integrate that hard IP into their processors.

That initiative has never taken off, so eventually Intel kicked off its SoFIA (Smart or Feature Phone on Intel Architecture) joint SoC development program that enabled third parties to use Intel Atom cores and modem technology (implemented using TSMC's 28nm node) in their application processors for handsets. While both Rockchip and Spreadtrum eventually came up with their SoFIA 3G and SoFIA 4G SoCs based on Airmont cores and made on TSMC's 28nm technology, both processors were released in 2015, had to compete against SoCs made on Samsung's 14nm-class node or TSMC's 16FFC node, and never got popular. Ultimately, Intel produced an eight-core Spreadtrum SoC at its fabs using its 14nm manufacturing technology, but that processor also failed on the market.

As a result, Intel licensing a CPU core to a third party is a very rare occurrence these days and the first in this decade. The reasons behind the move are completely unclear because the RosaicLabs startup is two months old, it cannot pay Intel cash, and its commercial prospects are completely unclear. While one may argue that now that Rosaic has access to x86 cores, it is not going to pursue Arm or RISC-V cores, keeping in mind that hundreds of startups choose Arm or RISC-V every year, addressing one startup does not enable Intel to expand its x86 share compared to Arm or RISC-V tangibly.

In any case, for now, the deal between Intel and RosaicLabs leaves more questions than answers, mainly because all we know about RosaicLabs is that it is led by an old acquittance of Intel's chief exec, Lip-Bu Tan.

New FCC legislation against foreign-made advanced robotic devices may have inadvertently introduced a ban on non-U.S. robot vacuums from being imported into the United States, according to The Verge. The FCC has added foreign-produced advanced robotic devices and connected power inverters to its Covered List, blocking new models from the equipment authorization they need before they can be imported, marketed, or sold in the United States.

The four-part test buried in the underlying national security determination catches any ground-traveling robot heavier than 4.4 pounds, including its dock, provided it carries an environmental sensor and a network link running at 200 kb/s or faster, and it names "AI or machine-learning model weights" as covered software. The determination, attached as Appendix C to the FCC's public notice, applies to a mechanical mobile device capable of locomotion, obstacle avoidance, navigation, or movement on the ground that operates at a distance from a human operator.

Devices qualify only if they also contain all three of a sensor that perceives its environment, a wired or wireless connection capable of at least 200 kb/s in either direction, and software controlling autonomous navigation, perception, data collection, or remote command and control. Bluetooth satisfies the connectivity test, as do Wi-Fi, cellular, and satellite. FCC media relations director Katie Gorscak confirmed to The Verge that robot vacuums meet the definition.

Six categories are exempted: connected vehicles of any gross weight, rail vehicles, uncrewed aircraft, uncrewed underwater vehicles, FDA-regulated devices including surgical systems and powered wheelchairs, and fixed industrial arms such as SCARA, delta, and gantry designs. Drones were placed on the Covered List separately in December.

Both determinations define "foreign-produced" as anything failing to qualify as a domestic end product under 48 CFR § 25.101(a), the Buy American Act rule. Under that provision, an item must be manufactured in the U.S., and the cost of domestic components must exceed 65% of the cost of all components for goods delivered through 2028, rising to 75% from 2029.

The same paragraph waives the component test for commercial off-the-shelf items, which would leave only the U.S. manufacturing requirement for a mass-market consumer robot. Manufacturers can apply to the Department of Defence for a Conditional Approval that lifts the restriction, a process that both Netgear and Amazon's Eero brand cleared within weeks of March's router ban.

Covered List status blocks Class I and Class II permissive changes under 47 CFR §§ 2.932(b) and 2.1043(b), the mechanism manufacturers use to push firmware and security fixes to certified hardware. The Office of Engineering and Technology suspended those prohibitions for robots and inverters hours after the listing, repeating the relief it gave drones in January, routers in March, and both categories through 2029 in May.

We've seen with DJI just how damaging an entry on the Covered List can be. The company disclosed in an April court filing that the FCC revoked authorizations for 14 existing products and blocked 25 planned 2026 launches, and Chinese customs data reported by Nikkei Asia showed civilian drone exports to the U.S. down 60% to 70% year over year since December. DJI is suing over the designation.

Have you ever felt like you need more keys and/or mouse buttons, despite rocking a full-size keyboard and a mouse with way too many buttons?

Don't worry, you're not alone. I constantly find myself running out of shortcut keys, especially when I'm working across multiple programs. Sure, most gaming peripheral softwares these days have an option that lets you program different inputs for different apps, but this requires said software to be open, running, and working as intended when you switch between apps. And as someone who has a lot of experience with gaming peripheral software, I can confidently tell you that this is an extremely tall ask — better to just buy a bunch more buttons.

Enter: the standalone macro pad. An extra set of programmable keys/buttons/knobs /dials/other inputs that you can use alongside your keyboard and mouse. I'm talking about everything from the ultra-basic plug-in 10-key numberpad to a Stream Deck you can control with your feet. They're incredibly useful for streamlining your workflow... if you make use of them.

That's the thing about macro pads — like 19-button mice and dedicated macro keys on keyboards, they require some forethought and setup if you're going to incorporate them into your life. These days, they typically come with a specific purpose in mind — 10-key numberpads, for example, are designed for people who do a lot of data entry, while streaming decks like Elgato's Stream Decks are designed for streamers who need to perform a series of tasks while they're in the middle of playing games and interacting with viewers. But you don't need to be an accountant or a streamer to incorporate a macro pad into your life; you just need to be a little creative.

But first, let's take a look at the options:

▶️ The 10-key numberpad

A 10-key numberpad is technically only a macro pad in the sense that many games and apps let you program shortcuts within them, and numberpad numbers count as separate inputs from alphanumeric numbers. You can pick up a standalone 10-key numberpad for pretty cheap — here's a wireless one for $10 — though, of course, that won't get you much in terms of customizability or typing experience. For a little more, you'll find numberpads that are similar to our favorite mechanical keyboards, with hot-swappable PCBs, mechanical switches, gasket mounting, and customizability, such as this one from $36 Epomaker EK21 numberpad or this $34 8BitDo 18-key numpad.

We also recently took a look at the Turtle Beach KP7, which is technically a numberpad. However, this also has extra keys and a programmable knob, which takes it into "gaming pad" territory — see Razer's Tartarus line. As for when you actually need a 10-key numberpad and not just 10 keys that are not a numberpad, there are a few specific scenarios: data entry (anyone who performs data entry knows this is significantly faster), certain applications (3D modeling programs, such as Blender, often have a lot of numberpad shortcuts), and alt codes for quickly entering special characters (although perhaps my editors would prefer I not be able to quickly enter Alt + 0151). Outside of these scenarios, however, you probably don't need a numberpad, specifically. And while you can remap numberpads, or even assign macros using programs such as AutoHotKey, you can also just get a non-numberpad macro pad.

▶️ The non-numberpad keyboard

Customizable non-numberpad macro pads come in all shapes and sizes, from mini three-key pads to larger ones with knobs and dials, such as this DIY Raspberry Pi-powered pad we looked at a few years ago. (I will point out that something like The Shrimp keyboard we reviewed a couple of years ago is not a macro pad, as it replicates existing keys and can't be used in addition to a regular keyboard.) These types of macro pads only get so big, however, because there's a limit to how many random, unorganized keys you can have and keep track of. That's why larger macro pads tend to be streaming decks with LCD keys (and various other inputs).

▶️ The streaming deck

Streaming decks — which include, but are not limited to, Elgato's products with the same name — are customizable macro pads with LCD keys, or several buttons placed over a single LCD screen. The keys are dynamic, with images that update to reflect what they're currently assigned to do, and can also be set to display information such as time, date, weather, PC stats, etc.

Streaming decks are also (usually) supported by more robust, dedicated software that allows for more advanced tasks than typical macros. You can, for example, set up chains of complex events, such as opening several programs in a specific order, or changing a series of settings. They're also often designed to work with existing apps and programs, so they can be a little easier to incorporate if you happen to be using said apps/programs.

Streaming decks also often feature other types of inputs, such as touchscreens, rollers, knobs, dials, and sliders. Some are even modular, like Cooler Master's MasterHUB, which lets you swap sliders for knobs and dials. Of course, the type of input you need will depend on what you're doing — a knob or a dial is great for things like changing brush sizes in image editing apps, scrubbing through video in a video editor, or adjusting settings like volume or brightness. Sliders are good for adjusting multiple things — such as microphone volumes, in a podcast — quickly and simultaneously. Touchscreens aren't my ideal input in most situations, but they can be useful for swiping through "folders" of buttons on a streaming deck (especially since it means you don't have to "waste" a button on being able to move between screens).

It's not hard to see why streaming decks are aimed at streamers, podcasters, and other content creators who are trying to do multiple things on their PCs at once while also trying to be present and interact with their audience. Or why certain programs, such as photo/video/audio editing software and 3D modeling software, benefit from having extra keys. But you don't have to be creating media in real time or in a shortcut-heavy program to find ways to use your macro pad. Here are some of the ways I use my macro pad(s):

Basic (short) shortcuts

Shortcuts only exist because we have a limited number of keys. It's not better to use a shortcut and press two or three keys when you could just press one key (plus, it's not particularly ergonomic to stretch your hands across the keyboard all the time). Any shortcut you use frequently should be programmed into a macro key. Some of the ones I use are:

• Moving between tabs - (Shift + Ctrl + Tab / Ctrl + Tab) I program this to a knob so I can just skip through my tabs.
• Close current tab - (Ctrl + F4)
• Open last closed tab - (Shift + Ctrl + T)
• Move current tab right / left - (Shift + Ctrl + PgDn / Shift + Ctrl + PgUp)
• Select address bar - (Ctrl + L)
• Zoom - (Ctrl + - / Ctrl + +) I also program this to a knob.
• Switch apps - (Alt + Tab)
• Select all - (Ctrl + A)
• Copy / Paste - (Ctrl + C / Ctrl + V)
• Find - (Ctrl + F)
• Left click - sometimes I need to click something without moving my mouse.

Opening specific websites / programs / folders

The nice thing about a streaming deck setup is that I can group things together — I can put the apps I commonly use at the same time on one "page," so everything is right there when I want to use it. I can also program a series of tasks to one button, so I can have multiple applications open at once if I always use them together.

Changing obnoxious Windows settings

This might be more of a "Tom's Hardware peripherals editor" thing, but I constantly find myself switching between various devices — audio devices, webcams, etc.

Entering text strings

There admittedly aren't a ton of text strings I use so frequently that I find typing them inefficient, but there are some — for example, hashtags on social media (on the rare occasion I use social media), or 'site:tomshardware.com ' for when I need to find an article on our site.

Extra function keys

If I'm using a keyboard that doesn't have a function row or doesn't have enough of a function row, I often just use my macro pad as the function row. This is useful in apps and games that already have function row shortcuts built in, or that have single-key programmable shortcuts.

Organizing my desktop

I have four monitors, so it's easy to lose things all over my desktop. I can use plugins to automatically snap windows to certain positions or automatically organize all windows on one screen into a predetermined layout.

I do some photo and video editing, as well as some 3D modeling, but not enough that I can really justify setting up a macro pad just for that. But I'm sure everyone reading this uses at least several basic shortcuts that could definitely be programmed to a macro pad — and that doing so will make more of a difference than you think.

When I had a kid, I found myself taking a lot more photos. When a baby lies on its back considering a ceiling fan for half an hour, you can suddenly find yourself with dozens of cute shots. And it doesn't stop when they grow up.

At a certain point, this bounty of photos weighed on me. I would look at my photo library on my phone or computer and worry about what would happen if something went wrong. It was time for a backup methodology more advanced than plugging in an external drive a few times a month.

At first, I thought about a NAS, which seemed like the obvious solution. But as I researched (and saw how expensive HDDs are these days), I opted for a mini PC. I was lucky enough to score a Mac Mini with M4, 16GB of RAM, and 256GB of storage on Apple's refurbished store a few weeks before the company raised its prices. The best time to buy it would have been at $399 on sale at MicroCenter. The second best time was when I did it.

An M4 Mac Mini is overkill for my project. M1 would've done the job. Any number of older Intel- or AMD-based mini PCs would've been sufficient, and most homelabbers rely on Linux or even Windows for a reason. The M4 will future-proof this machine. It is, though, admittedly funny to me that one of the most powerful computers in my home is running headless in a closet.

But the Mac has other benefits. For one, my home has a lot of Apple products in it. While I'm equally comfortable with Windows and macOS, my wife is exclusively in Apple's ecosystem. So when I realized I would want this system to back up her photos and documents too, making that easy was important. I'm able to access it from either my MacBook Pro or my custom-built PC over VNC or SSH on the command line. There are a few other benefits of using macOS if you have other Apple devices in your home.

My overkill hardware

The M4 Mac Mini is far more than this project needs. But on the plus side, it should see support for a long time. And frankly, getting one during the shortage was just kind of a thrill.

The 256GB of storage is being used exclusively for the operating system and any applications. All of my actual data is on a series of external drives, most of which I already had lying around. That includes a 4TB PCIe NVMe SSD and 2TB PCIe NVMe SSD in enclosures (the former with Thunderbolt 3). But I also wanted a spinning hard drive for longer-term storage. For that, I opted for a Seagate FireCuda Vault X, which isn't the cheapest option, but can connect over USB-C bus power without the need for external power.

All of this is hidden on the top shelf of a closet. This isn't the ideal space, but it's the only one that will work. I live in an apartment, and that closet is where the sole Ethernet connection comes in. I already had my router and modem there. I've hooked up the Mac Mini to the router, connecting it to my home network.

The Mac Mini runs non-stop. That's good, because the power button is on the bottom, and I'd hate to have to pick it up every time I want to shut it off. (Also, I need a step-stool to reach that shelf.)

Backups and redundancy

The SSDs and HDD are all connected to the Mac Mini via the system's USB-C ports. The Thunderbolt enclosure and the HDD are attached to Thunderbolt 4 ports on the rear (the latter to ensure it gets the wattage it needs), while the 2TB SSD in the USB-C enclosure is connected to a 10GB/s USB-C port on the front.I've put too much thought into each drive's purpose.

The main drive is the 4TB USB-C drive, which has two volumes on it (unlike partitions, which macOS also allows, volumes are more flexible with free space). My main volume is for extra copies of important documents, my Apple Photo library, and also for backups of photos I keep outside of Apple's library (I have a tendency to clean house every few years). If I create any files I want to back up on my Windows PC, this is where I go to back them up on site. And lastly, I have a folder just to store files that aren't critical but that I might want to access from any machine. Why keep them on my laptop when I have terabytes of storage to play with?

But the second volume, which is just a small portion of the drive, is also for excess data I don't want to keep on the internal drive. At the moment, that's largely dedicated to macOS content caching (see below).

My 2TB SSD is for Time Machine backups. I can use macOS's built-in backup tool over the network to back up my laptop without plugging anything in.

The HDD is a redundancy play. That's currently split in half — one volume as an alternate Time Machine destination (letting me switch between the SSD and HDD), and the other volume is a copy of my important documents and photo library, which is cloned each night using Carbon Copy Cloner.

This is all in my home, of course, so if my computers and Mac Mini were in the same fire, much of my data would still be lost. Without an offsite backup, I would be in violation of the 3-2-1 backup rule (three backups on two storage devices, with one of them offsite). I keep many of my most important photos and files elsewhere in the cloud, in a mix of iCloud, Google Drive, and Dropbox. It's not a great system, and could use improvement, but it's better than nothing. If HDD prices were to go down, perhaps I could replace the Vault with another one and swap them once a month, keeping the other at a family member's home.

Running headless

I could put a monitor on the top shelf of my closet, but I've opted for a better model: running the Mac Mini headless.

Mostly, this meant setting up the Mini (with a monitor, naturally), to prepare it before booting it up. For me, this included removing a lot of the iCloud syncing it would normally do (I only want it downloading my original, full-sized photos from iCloud, but it doesn't need to get texts), preventing automatic sleeping, allowing for file and screen sharing on the network, and making security decisions that allow me to access the system and files remotely and securely while also deciding how often I want to have to take the thing down from the closet to log back in with a password.

From another Mac, it's very easy to use virtual network computing (VNC) via the built-in screen-sharing utility. From Windows, I can still use a program like RealVNC to access the desktop. I also reduced motion and graphics, set a solid color background, and made other tweaks in an attempt to reduce the amount of data or lag I might see over a remote connection.

There's also the option for SSH. I'm still working to be a bit more proficient at the command line, but you can do that either in macOS in the Terminal or Windows in the Command Prompt or PowerShell.

I've also seen that some people swear by running the Mac Mini headless by using an HDMI dummy plug to force high resolutions when remoting in. But using Mac Screen sharing, I haven't particularly had a problem.

Managing on the go

Typically, I'm more than OK with having what amounts to a backup server accessible locally. But what if I need a file that I'm storing on the server and I'm not at home?

For that, I've created a Tailscale network consisting of my laptop, the Mac Mini, and my iPhone. This gives each device a semi-permanent address I can access it through, as long as both are on the network.

That makes it easy enough from a laptop. Unfortunately, iOS doesn't have the super-easy Screen Sharing tool that macOS does. So on mobile, I have the RealVNC mobile app, which can access the Mac Mini either through the local address or Tailscale. Using a virtual desktop on a phone's touch screen isn't ideal, but it's not nearly as difficult as I thought it would be.

Mac benefits and drawbacks

Let's be clear: macOS is not designed for servers (macOS Server was discontinued in 2022). I am very aware that home networking purists would much rather use their preferred Linux distribution, or even Windows. And that's OK!

But if you have Apple devices in your own home, there are some benefits to having a Mac in your homelab.

My favorite of these is content caching, which can keep copies of macOS or iOS updates, App Store updates, or data stored in iCloud in the cache, so that they can be sent to other devices on a local network more quickly.

For those who are using macOS, it's nice to be able to use Time Machine, and mount other drives in the Finder the way you would with a Thunderbolt or USB-C drive and just have it on the desktop.

And yes, for management, the aforementioned Screen Sharing app is pretty solid, and it’s one less piece of software you need to worry about.

Additionally, the machine is whisper-quiet, rarely uses more than 3% of the CPU (and often less), and is efficient enough that I've noticed no substantial change to my electric bill.

The only real drawback for my use case is that while the M4 SoC will keep this project future-proof for a bit, adding RAM is impossible. I opted for the 16GB RAM / 256GB SSD model for budgetary reasons, but it's possible that, depending on what else I want to do with it, that could eventually hamper me down the line. It's especially the case if I ever want to get more into local AI.

However, once I get more advanced, there are some applications that would run more easily if I had gone for a Linux device. Instead, I'll need Docker or VMs.

What I need next

A project like this one is never truly finished. I have the Mac; I have it backing up my stuff (It ends up that after all this, I'm still working on getting my wife to back up her end). There's much more that I want to do down the line. Perfect, however, is the enemy of getting started at all.

One good item for this project would be a small uninterruptible power supply in the case of a power outage. Another would be a dock. A number of third-party companies make docks specifically for the Mac Mini that can fit an SSD, which might be a good way of organizing my cable mess. But if I ever switch computers, that dock will likely end up being less friendly for cable management.

There's also a whole bunch more I want to do with the Mac Mini. I don't have a ton of Smart Home equipment in my apartment, but what I do have is a mix of older Alexa-focused stuff. If I wanted to control that with Apple Home, I could try hosting Home Bridge. Or if I want to move to a more private system, I could install Home Assistant on the Mac Mini using a virtual machine.

I could also toy with PiHole, though again, I would have to use Docker or a Virtual Machine. That would let me block ads across my network (while whitelisting the ones I want to support, of course).

Further down my list are a Plex or Jellyfin server. I don't own that much physical media, but being able to access what I do have virtually could lead me to consider it among my subscription options. I could also use one of these to offload my MP3 collection from my laptop.

But for now, the file server and backups have given me some peace of mind. My photo library certainly isn't getting any smaller. I just hope storage prices fall before I need another drive.

Hop Aero, a six-person Y Combinator startup based in Orange, California, has published the first public details of what it calls ‘Rook,’ an autonomous rocket the company says will carry 550 pounds (250 kg) of cargo up to 750 km in about 15 minutes, launch from a standard 40-foot shipping container, and land on unprepared ground with no runway or fixed infrastructure. The company's Y Combinator listing gives Okinawa to Taiwan as the reference mission for that 15-minute flight and pitches Rook as a way to put swarms of autonomous unmanned systems on a battlefield. However, Rook hasn’t flown yet, and Hop Aero's only government funding is a single $1.25 million Air Force contract that expires in October.

A minimum-energy ballistic arc covering 750 km needs roughly 2.64 km/s at burnout and peaks near 181 km, by some quick napkin math, which puts Rook well above the 100 km Kármán line into space. The ballistic coast alone accounts for about six-to-seven minutes, leaving around eight of the claimed 15 minutes for boost, reentry, and landing. A 40-foot ISO container offers about 12.03 m of internal length and 2.35 m of width, capping the vehicle's dimensions. Rocket Lab's Electron stands 18 m tall and delivers about 300 kg to low Earth orbit.

The Air Force Research Laboratory made Rocket Cargo a Vanguard program in June 2021 and awarded SpaceX $102 million in January 2022 to work on the concept with Starship. Starship flew its 13th test on July 24, with the upper stage later splashing down in the Indian Ocean.

The Air Force renamed the effort Point-to-Point Delivery in its fiscal year 2025 budget request and asked for $4 million. A Johnston Atoll environmental review covering up to 10 reentry vehicle landings a year was suspended in July 2025, and Rocket Lab's AFRL reentry demonstration on Neutron hasn't flown yet. The Navy's answer to the same forward-supply problem is 3D printing spare parts at the deployment site.

Co-founder Jacob Balaj previously worked at Masten Space Systems, which ran more than 600 vertical takeoff and landing flights over 18 years and was developing its Xogdor vehicle for point-to-point payload transport when it filed for Chapter 11 in July 2022. Astrobotic bought the assets for $4.5 million that September.

Inversion Space, another Y Combinator company, raised a $44 million in Series A funding and employs around 60 staff, but its subscale Ray demonstrator failed to leave orbit in January last year after a short circuit stopped the deorbit engine from igniting. Hop Aero says it has completed one tethered test of a small-scale prototype at the Oklahoma spaceport. At the time of writing, no company has yet flown a licensed commercial point-to-point cargo delivery.

The Peaceful Outcome, a retro gaming solutions provider, has announced an SSD upgrade kit for the Wii U, allowing owners to increase the storage on their console from 8GB or 32GB to 1TB or higher. You get the kit for $21.99 on the TPO shop. It lets you internally attach a SATA or NVMe M.2 drive of various sizes so you can directly load your games on your Wii U without needing an external drive or to swap out DVDs. It also comes with a USB port that lets you transfer files to your SSD without needing to disassemble your console again.

You can already get a 3.5-inch SATA hard drive mounting kit at the same price (or a 2.5-inch kit for $17.99), but TPO said that it created the M.2 version for longevity reasons. It also noted that SSDs won’t give you a significant performance boost on the Wii U — an SSD loads just 7.5% faster than the DVD drive and 6% quicker compared to a hard drive — but it does give you more space to save your games on the console. TPO said that this does not offer any performance uplifts versus SATA drives, but it created this anyway because of easier M.2 NVMe drive availability in the future.

Note that this isn’t a straightforward upgrade — first, you have to provide your own drive, which could be one of the best SSDs you can get today or one that you already have lying around at home, and then you’ll need to break open your console to install the kit. This is the easy (and most expensive, given current storage pricing) part. Once done, you’ll need to hack into your console so that it can use the custom Aroma firmware. While there’s a complete guide on how to install it, it’s not without risk, as there’s a small chance that you could brick your device during the process.

If you’ve previously purchased a drive upgrade kit from TPO in the past, you could get updated parts to upgrade your current kit at shipping cost. All you need to do is upgrade the firmware on your interposer board, and you should be good to go.

While the Nintendo Wii U already accepts external drives, installing this upgrade kit will give your console more storage without needing to have a bulky drive hanging outside it all the time. This upgrade is more for aesthetics, but if you’re willing to accept the risk of (or already have) homebrew software, then finding a way to have a “permanent” storage upgrade on your Wii U is a no-brainer.

The largest utility company in Georgia is conducting a massive upgrade of its grid, and part of this project requires the connecting its Ashley Park Substation to Plant Wansley, which is currently undergoing an upgrade. The 35-mile stretch between the two facilities will go through Fayette, Heard, Fulton, and Coweta Counties, and require the removal of 30 residential properties along its path, reports Fortune. This included Ansley Brown’s family home, who took to Instagram to share her story.

“Georgia Power is forcibly taking people’s homes, okay? They have no choice in this matter,” Brown said in her IG post. “As you can see behind me, these are the power lines, and this is my childhood home. My childhood home is being taken by Georgia Power — they’re going to bulldoze this entire property to the ground. We don’t have a choice in this. They’re going to be expanding these power lines. Why? For the data centers. All of this is for the data centers.”

Thankfully, her family was able to get in touch with their representative, Brian Jack (R-GA), who sent people on the ground to take stock of the situation and connected the two parties. Brown said in her last update that they’ve already settled with Georgia Power, with the company telling Fortune that the family has agreed to a settlement for an undisclosed amount.

While this ended up on a somewhat positive note for the family, this is an example of what one report previously warned about government using eminent domain to seize land for the AI infrastructure build out. Georgia Power isn’t exactly building the transmission line to connect a power plant directly to a data center, but AI data centers’ massive power demands have caused massive opposition to projects like this to appear nationwide. It also doesn’t help that an AI data center, which is being accused of secretly using up 29 million gallons of water, sits less than five miles to the southwest of the substation.

The current administration has been pushing for AI data centers, believing that it needs all that infrastructure so it can win the “AI race” against China. However, the U.S. power grid is sorely lagging behind its Asian rival, meaning U.S. power utilities and electricity providers are spending billions of dollars to upgrade the grid. This, in turn, is being passed on to every power consumer, which is heavily affecting the average American. President Donald Trump instituted and expanded the “ratepayer protection pledge” in attempt to control the spiraling costs.

California has been trying to pass a law that will codify these promises, but the same tech companies that signed the pledge are also reportedly lobbying against the bill. At the moment, Oregon is the only state that has a regulation that forces big consumers (like data centers) to pay their fair share, with industries using 20MW or more getting slapped with a 30% increase in their power bill while residents and commercial users get their costs slashed by 1.3%.

Legendary Windows developer Dave W. Plummer has shared details and screenshots of a version of Task Manager for Apple Mac computers. Apple computer users currently have Activity Monitor for peeking at CPU activity, memory usage, as well as closing apps and processes, by default. However, “Activity Monitor blows,” asserts Plummer, in response to people asking why he would port the classic Windows utility to the fruity computer.

Preempting questions from his social media followers, Plummer mused over the optics of releasing Task Manager for Mac, due to his Microsoft development history. In case you missed it, Plummer was the original dev behind Windows Task Manager when it debuted as a lean and mean 80KB accessory. He’s also recently reimagined this essential Windows system tool in a retro-futuristic Atari Tempest remix.

Back in the world of Macs, and looking to the side from the world of PCs, there is indeed a case for a better task manager or activity monitor for Apple computers. The Windows utility has more features under the hood, giving it a far greater scope and utility value (task priorities, startup management, services control, and more). We haven’t tried the new Mac version of Task Manager; it hasn’t been released at the time of writing, but if it can decant some of the Windows features over to the Apple computing platform, it may be an attractive addition.

Plummer says the utility is currently in beta, and he intends to “throw it up on the App Store… (for free in Beta, because the first taste is always free).” There’s also, admittedly, a chance he will get bored with tinkering with it and release the source for others to continue with.

We already mentioned the optics over a seasoned Windows dev coding / porting staple Microsoft OS code to Apple Macs, but Plummer has addressed queries about this in further posts today. In this Tweet, the dev asserts that “Microsoft very graciously sent me the source code to XP Task Manager along with permission to share/demo it.” Moreover, the project is written in Swift and uses no original code, and Plummer says he has no post-Windows XP code to tap into, either.

Meanwhile, development continues apace, with Plummer providing insight into some drive meter activity coding he’s currently working on. The dev is finessing drive activity for Task Manager for the Mac right now and pondering over the flickery visuals resulting from “drawing instantaneous drive activity at 60fps.”

Despite the storage shortages, a brave team of Minecraft players has successfully mapped the entirety of 2b2t, arguably Minecraft’s oldest and most notorious server, and have now shared it as a 15TB download of highly compressed data that can be unpacked to the full 80TB archive. The team had to create its own custom compression format to pull off the feat.

The 2b2tplace preservation project started in 2024 and finally concluded in April of 2026 after an intensive 22 months of hard work. The team employed 28 bot accounts that tirelessly flew across the vast 2b2t world to map every single block with precision. The sheer scale of 2b2t is staggering because it encompasses well over one million blocks and includes the three primary Minecraft dimensions: the Overworld, the Nether, and the End.

The 2b2t server has a data footprint that exceeds 80 TB. Even if the team began their efforts before the recent storage shortage, it would still require an immense amount of storage capacity. Storing the entire 2b2t server would demand at least eight 8TB M.2 SSDs or, as an alternative, five 16TB SATA SSDs. Even with traditional storage, you still need three massive 36TB hard drives. We estimate the team has likely spent several thousand dollars on storage equipment, not to mention priority queue purchases and server rental costs, which totaled over $3,000 alone, according to the GitHub page.

If you are not a big Minecraft fan, 2b2t, short for 2builders2tools, is a Minecraft server characterized by its anarchic nature that launched in 2010. Unlike typical Minecraft servers, 2b2t operates with absolutely no rules, no staff moderation, and no map resets, so players have complete freedom to do whatever they want. Over the years, countless updates have dramatically reshaped the landscape, which has fueled several enthusiasts, including crayne, Fuch, mahan, Steve3, and others, to preserve the original state of 2b2t before it loses all of its essence for good.

Storing or sharing 80TB of data is insane, especially given the limited availability and overpriced storage solutions today - something on the scale of 2b2t can rapidly cause file sizes to spike to impractical levels. The archival team originally promised back in April to make the archive available in a compressed format, but that obviously created issues. As such, the team engineered a custom file compression format specifically for this project, named .zvcr (Zstd-compressed Version Controlled Regions). Common Minecraft servers use the .mca (Minecraft Anvil) file format, which is fine for single-player worlds or even small servers.

Unlike the .mca file format, which normally uses Zlib or Gzip compression, .zvcr uses the Zstd (Zstandard) algorithm that yields higher compression ratios. Zstd is superior in every way to Zlib or Gzip, whether it be compression and decompression speed or final file size. As a result, the team was able to compress the entire project to 15TB, saving up to 81.25% of space. So, now instead of needing eight 8TB M.2 or five 16TB SATA SSDs, you only need two or one to store the compressed archive, respectively. Unpacking the archive, on the other hand, is a different story.

The 2b2t server remains online so that Minecraft players can join in for their daily dose of chaos. Nevertheless, many longtime gamers argue the server has strayed from its anarchic roots. The eventual shift is the main motivation behind the 2b2tplace preservation initiative.

A firm that is using AI to locate ancient shipwrecks is sending out a call to seafarers to salvage sunken treasure. The general impression of the state of the tech job world might be that people are being fired left and right, and the only open jobs are AI-related. But what if you could use your sailing and diving experience all the same? That's what AE Studio, a software consultancy and AI research firm, is looking for: a literal pirate to hunt for treasure in the ocean. The work location is "extremely remote."

The requirements are quite extensive, requesting a lifetime of nautical experience, diving certifications, and the ability to do so "in conditions insurance companies decline to cover," plus bureaucratic handling of permits, ports, and sea creatures. Bonus ballast includes having pre-1800 salvage experience, proficiency in Spanish, Portuguese, and Dutch, sailing certifications, owning your own dinghy, and "operational experience in Somalia, Hormuz, or Malacca" — clearly indicating this job is not for the weak of mast or faint of sail.

Applicants ticking all the boxes in the cargo manifest can expect a compensation package inspired by 17th-century privateer commissions: equity in this new venture (retained when it's spun off AE Studio Skunkworks), cash "weighted heavily toward upside" of the $50k-$500k range, and a share of the plunder. The company handles logistics and legal costs.

If by now you're wondering what this has to do with AI, the explanation is fairly simple: AE Studio claims it's using AI to go through 80 million pages of records spanning five centuries of Spanish colonial paperwork. The data includes nautical, admiralty, and insurance writings, and the final goal is to locate lost shipwrecks and their sweet, juicy booty in the areas most likely to contain them after cross-referencing the info.

As "the model does not swim," prospective buccaneers act as the proverbial robot arm for the actual search-and-plunder operations. The firm does warn that the first few dives are bound to result in empty hands. Amusingly, AE Studio appears to draw a mathematical parallel between the reward of falsifying historical records to hide treasure and incentive-driven alignment failures in AI training.

AE Studio went as far as to post a quartet of not-really-hidden coordinates of potential work sites. Drawing on my Portuguese lineage as a bona fide sailor (and totally not on Claude's research abilities), the sample spots in question likely refer to:

• 24°52'14"N 81°39'08"W: west of Key West, Florida, the wreck site of Spanish galleon Nuestra Señora de Atocha, lost in a hurricane, in 1622.
• 27°21'02"N 80°17'55"W: Florida's "Treasure Coast", where eleven Spanish ships went glub-glub in 1715.
• 15°04'31"N 75°58'12"W: off of Cartagena, Colombia, seemingly part of Spanish shipping lanes; 1739.
• 06°12'47"S 38°22'04"E: the only dry-land point near the coast of Tanzania; 1798.

Despite its whimsical and playful nature, the job listing is real, and AE Studio's Skunkworks division is known for its off-the-wall projects. As the description mentions equity and profit sharing on recovered booty, it's possible, if not likely, that the project eventually becomes its own subsidiary, attracting entrepreneurial pirates. I was looking for a career change, anyway, and it's good to revisit my roots.

Plymouth Township, which sits roughly 13 miles to the north of Philadelphia, said that it will approve a new data center project on the condition that it meets 43 specific demands. While Pennsylvania state law prohibits blocking a landowner from using their property lawfully, Ars Technica says that townships can impose zoning restrictions and health and safety regulations. Because of this, Plymouth created a nine-page plan that covers everything from noise, light, and air pollution, to water and power use, as well as land use, taxes, and even future decommissioning of the data center.

Many jurisdictions would have just outright rejected or delayed the data center project, which is owned by Brian O’Neill, but Plymouth Township decided to go in a different direction. It still allowed the application to go through, as not doing so would expose the local government to legal action, but gave the developer the outlined demands (listed in pages 4 to 12 of this PDF) that it needs to meet to get the green light from its people. The township said that the applicant initially showed that they would implement that township’s provisions, which were derived from the demands of its residents.

“The Council can, should, and will do everything in its power to ensure the health, safety, and welfare of the Township, our environment, and our residents. This is always our top priority,” Council President Lynne Viscio said in a statement. “We understand that a hyperscale data center raises numerous significant concerns, issues, and questions. Accordingly, we spent considerable time researching and developing a comprehensive set of requirements to address the concerns raised by residents, our own concerns, and the issues raised by other subject matter experts.”

Unfortunately, the data center developer rejected the concerns after seeing the breakdown of demands. It then filed a second application challenging the provisions set in the zoning ordinance, saying that they make building the project “too difficult” for the developer. Plymouth Township did not look kindly upon this, saying it “is a blatant attempt by the Applicant to demand approval by tantrum.” It’s currently unclear how Plymouth Township will move forward with the issue, with the application currently awaiting approval from the Zoning Hearing Board.

As for O’Neill, he told the Philadelphia Inquirer that the accusations of was part of a “misinformation campaign” against his project, and that he has been “negotiating in good faith” with the township’s attorney and had even agreed to most of the provisions. “We are sympathetic to the fact that they are under tremendous political scrutiny from people outside the township, as well as residents inside the township, and that makes giving a landowner their property rights … challenging,” he told the local newspaper. “However, I am a landowner, and I do have rights, and it is their job to be impartial and fair in their analysis and response.”

These requirements are meant to prevent the various challenges that other communities face with data center deployments. Examples of these include a Michigan data center generating noise 24/7 that has been affecting residents for over two years, PJM Interconnection, the U.S.’s largest power region, hiking electricity prices by 76% due to AI demand, a Meta data center contaminating a city’s reclamation water supply, and Elon Musk’s Colossus 2 data center facing a lawsuit for its unpermitted natural gas turbines spewing nitrogen oxides and other pollutants.

Xbox consoles recently experienced a worldwide outage, during which people were unable to access even disc-based games that should have been playable offline. Service was restored within a day but the impact of this discovery could be significant as tensions run high surrounding the crumbling state of physical media. Microsoft, however, was quick to suppress the negative PR, telling The Verge that discs should have never been affected by the outage in the first place.

"Disc-based entitlement checks should not prevent players from accessing their games and this is by design," said Microsoft tech chief Scott Van Vliet. He went on to confirm that discs go through license checks in the form of verifying entitlements. These entitlements determine what content a user is entitled to access, including when said user is offline, since they're saved directly on the console. Van Vliet clarified that the team caught an issue that stopped the consoles "from correctly using saved entitlements during the outage."

Xbox uses the Smart Delivery system for distributing games that automatically installs the best version of the title for your hardware. Smart Delivery has an alternative implementation called full-disc support, where developers can choose to put all executables of their game on the disc instead of relying on a license to digitally download content. That means when you insert the disc, there's no need to even connect to the internet as the file should be ready to run out of the box. That's precisely what failed to occur yesterday.

The outage itself affected everything from log-ins to application launches, and from online play to this strange issue of discs not running as intended. It was tied to an external service provider suddenly going down, and remaining down, for 16 hours. Xbox relied on that external provider for license and entitlement checks, so when a console failed to connect to those servers, it simply locked out players from accessing the game. It worked as fail-close mechanism instead of the fail-open it should have been, at least for discs.

If you're even a little bit tech-savvy, this probably sounds familiar to you as DRM checks have been a part of gaming for a long time. It used to be limited to just digital releases, but disc-based media has evidently fallen to the same problems as of late. The 100GB storage capacity of Blu-ray discs is a genuine limitation, but that's rarely the cause behind stories like this. Microsoft says it's already working on releasing an update to address this issue, but has not provided a timeline.

Sony faced similar vitriol earlier when the community discovered mandatory 30-day online check-ins had been added to PlayStation 5 and 4 consoles, but that claim was later refuted. In 2024 , Steam came under fire for ambiguity over perpetual licenses as well, which just goes to show that even the Valve isn't safe from this great evil. Now that PlayStation discs will cease to exist by 2028, concerns over ownership tied to physical media are growing every day.

Seagate is on track to start qualification of its hard disk drives featuring 50TB-class capacities in late calendar 2027, with shipments to follow in 2028, the company announced this week. Demand for HDDs is so strong because of the rise of AI and continued strength of the cloud computing business that most drives are sold out through 2028 and negotiations about allocations for 2029 are ongoing.

"Mozaic 5, our 5+ terabyte per disk platform, remains on track for qualification shipments in late calendar 2027," said Dave Mosley, chief executive officer of Seagate, during the company's earnings call with financial analysts and investors.

Mozaic 5 is the company's 3^rd generation platform for commercial hard drives based on Seagate's heat-assisted magnetic recording (HAMR) technology that succeeds Mozaic 3 and Mozaic 4. The Mozaic 5 platform enables the company to build platters with over 5TB capacity and consequently build 10-platter HDDs with over 50TB capacity featuring conventional magnetic recording (CMR) for clients seeking performance and versatility or shingled magnetic recording (SMR) for clients that need maximum capacity to maximize their storage density.

If Seagate preps to initiate 'qualification shipments' of its 50TB-class hard drives in late calendar 2027, then it means that by the time the HDDs have passed all the manufacturer's internal validations, including reliability and durability of heads and media, shock and vibration tests, and longevity tests among many others. It typically takes server OEMs about two to six months to qualify new HDDs for their offerings, whereas hyperscale cloud service providers usually qualify them for six to 12 months. In any case, it is safe to say that Seagate is on track to ship 50TB-class hard drives in calendar 2028 with significant volume ramp in 2029.

These 50TB-class HDDs will come to market just in time to meet exabyte demand from the AI and cloud sectors. Most of Seagate's nearline HDDs have been allocated for 2027 and 2029 under long-term supply agreements (LTAs), with some customers looking to secure supply in 2029.

"Based on the long-term supply agreements in place today, the vast majority of our nearline exabytes are now allocated into calendar 2028," Mosley said. "[…] As our strategic relationships deepen, many are actively seeking to extend planning horizons through 2029 and beyond, which we believe reflects growing confidence in their own long-term infrastructure needs."

Seagate's LTAs not only define exabytes, but also product configuration and prices. As it turns out, both are set for the 'entirety of calendar 2027.' Meanwhile, Seagate is flexible on pricing of drives that are not covered by LTAs as well as newly signed LTAs, so the company is implying price increases, following makers of 3D NAND and SSDs.

"We continue to execute our value-based pricing strategy, balancing a stronger demand environment with our objective of supporting sustainable, profitable growth over the long term," Mosley said.

"Our volume was a little bit higher in fiscal Q4," said Gianluca Romano, chief financial officer of Seagate, during the call. "We think can be maybe a little bit of output available in fiscal Q1. Of course, we are pricing that increased output at a very good price right now."

The key advantage of Seagate's high-capacity drives based on the company's Mozaic platforms is, of course, its HAMR technology, which is gradually increasing its share within the company's nearline HDD shipments. HAMR-based products accounted for a 40% exabyte share of Seagate's nearline HDDs as of early July and are on track to account for 70% of the company's nearline exabytes shipments by early July 2027. Moreover, nearly half of Seagate's nearline capacity will rely on its 40TB-class HDDs featuring its Mozaic 4 platform.

"We expect to achieve our next ramp milestone by exiting calendar 2026 with 50% of our HAMR exabytes on our Mozaic 4 platform," Mosley said.

For the fourth quarter of its fiscal 2026 ended on July 3, Seagate earned $3.629 billion, up from $2.444 billion it earned in the same quarter a year ago. The company's gross margin totaled 52.3%, up from 37.4% in Q4 FY2025, and its net income reached $1.294 billion. The company's FY2026 revenue was $12.195 billion, up from $9.097 billion in the prior year. The net income increased more than twice year-over-year to $3.184 billion, with gross margin reaching 45.6%.