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BenchLM

Data as of September 30, 2026 · How the score is built

CurrentOpen WeightReasoning

Released Aug 3, 20261M contextQwen3.8-2.4T-A95B model card

Qwen3.8 Max

Decision readingQwen3.8 Max scores 72.1 out of 100 and ranks #16 of 211. This profile shows 60 source-displayable benchmark rows; its strongest eligible category is Multimodal & Grounded at #5. No comparable first-party API price is published in the catalog.

Released Aug 3, 2026 — see all recent releases

Decision snapshot

Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.

Capability

72.1/100

field median 52.4#16 of 211 ranked models

Public

#16of 211

Verified #9 of 74

Price

API rate not published

input median $1No comparable first-party hosted token rate

Speed

39tok/s

field median 89 tok/sFirst token 53.87 s

Context

1Mtokens

field median 256,000Maximum output length is tracked separately

Strongest published evidence

Multimodal & Grounded ranks #5. Particularly strong for screenshots, documents, charts, and grounded multimodal workflows.

Validate before choosing

60 published rows leave some tracked benchmark slots empty. No comparable first-party API token rate is published.

Source-linked · 60 displayable benchmark rows

Follow model changes

Category score record

Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.

Category scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticRank #14 of 119Percentile 89thWeight 22%15 benchmarksVerified
65.4
CodingRank #30 of 144Percentile 80thWeight 20%12 benchmarksVerified
55.4
ReasoningRank Not rankedWeight 17%2 benchmarksVerified
87.7
MultimodalRank #5 of 49Percentile 92ndWeight 12%24 benchmarksVerified
88.4
KnowledgeRank #23 of 170Percentile 87thWeight 12%6 benchmarksVerified
66.1
MultilingualWeight 7%0 benchmarksNot measured
Not measured
Inst. FollowingRank #16 of 124Percentile 88thWeight 5%1 benchmarkVerified
90.5
MathWeight 5%0 benchmarksNot measured
Not measured

60 of 496 tracked benchmark slots have displayable evidence · bars run 0–100

Coverage details

How much of this is verified

Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.

  1. Agentic15/15 verified
  2. Coding12/12 verified
  3. Reasoning2/2 verified
  4. Multimodal24/24 verified
  5. Knowledge6/6 verified
  6. MultilingualNot measured
  7. Inst. Following1/1 verified
  8. MathNot measured
Verified sourceProvisionalNot measured

Capability shape

Each axis shows percentile within that category’s eligible cohort. The comparison outline is the median of the six nearest public-score peers; a collapsed vertex means the category is not rank-eligible.

Qwen3.8 Max category percentile values

  • Agentic89th percentile
  • Coding80th percentile
  • ReasoningNot eligible
  • Multimodal92nd percentile
  • Knowledge87th percentile
  • MultilingualNot eligible
  • Instruction following88th percentile
  • MathNot eligible

The dashed outline is median of 6 nearest peers.

Eligible category ranks

  1. Agentic#14/119
  2. Coding#30/144
  3. ReasoningNot ranked
  4. Multimodal#5/49
  5. Knowledge#23/170
  6. MultilingualNot ranked
  7. Inst. Following#16/124
  8. MathNot ranked
Top decileTop quartileMid-fieldNot eligible

Benchmark ledger

Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.

Coding12 rows
Coding benchmark values, best verified comparison, weight, and source status
SWE-bench ProScore67.7%Versus best verified row

Best verified: Claude Opus 5.5 · 89.9%

Gap22.2 behindWeight26% ref. weight
FrontierSWE v2Score15.8%Versus best verified row

Best verified: GPT-6 Astra · 65.5%

Gap49.7 behindWeight8% ref. weight
LiveCodeBench (Vals)LiveCodeBench, Vals AI runScore87.9%Versus best verified row

Best verified: Claude Fable 5.1 · 90.5%

Gap2.6 behindWeight8% ref. weight
VulcanBench v3Score81.2%Versus best verified row

Best verified: Grok 4.5 · 89.9%

Gap8.7 behindWeight3% ref. weight
DeepSWEScore56.6%Versus best verified row

Best verified: Gemini 4 Argon · 77.9%

Gap21.3 behindWeightDisplay only
Terminal-Bench 2.1Score86.6%Versus best verified row

Best verified: SWE-2 · 92.8%

Gap6.2 behindWeightDisplay only
NL2RepoScore55.9%Versus best verified row

Best verified: DeepSeek V4.1 Flash · 65.4%

Gap9.5 behindWeightDisplay only
FrontierSWEScore73.5%Versus best verified row

Best verified: Kimi K3 · 81.2%

Gap7.7 behindWeightDisplay only
MLS-Bench LiteScore41.0%Versus best verified row

Best verified: Kimi K3 · 48.3%

Gap7.3 behindWeightDisplay only
PaperBenchScore93.0%Versus best verified row

Best verified: Qwen3.8 Max · 93.0%

GapBest verifiedWeightDisplay only
OpenHarmony BenchOpenHarmony Bench v1.0Score60.8%Versus best verified row

Best verified: Qwen3.8 Max · 60.8%

GapBest verifiedWeightDisplay only
SWE-bench (Vals)SWE-bench, Vals AI runScore85.6%Versus best verified row

Best verified: Claude Opus 5 · 97.0%

Gap11.4 behindWeightDisplay only
Agentic15 rows
Agentic benchmark values, best verified comparison, weight, and source status
OSWorld-VerifiedScore86.1%Versus best verified row

Best verified: Qwen3.8 Max · 86.1%

GapBest verifiedWeight6% ref. weight
Terminal-Bench 2.1 (Vals)Terminal-Bench 2.1, Vals AI runScore67.4%Versus best verified row

Best verified: GPT-6 Astra · 87.3%

Gap19.9 behindWeight3% ref. weight
OSWorld 2.0Score19.4%Versus best verified row

Best verified: GPT-6 Astra · 72.6%

Gap53.2 behindWeightDisplay only
Terminal-Bench 2.1Score86.6%Versus best verified row

Best verified: SWE-2 · 92.8%

Gap6.2 behindWeightDisplay only
JobBenchScore53.4%Versus best verified row

Best verified: Muse Spark 1.3 · 64.9%

Gap11.5 behindWeightDisplay only
AutomationBenchScore27.3%Versus best verified row

Best verified: DeepSeek V4.1 Flash · 54.8%

Gap27.5 behindWeightDisplay only
Agents' Last ExamScore52.4%Versus best verified row

Best verified: GPT-6 Astra · 59.3%

Gap6.9 behindWeightDisplay only
Toolathlon-VerifiedScore72.5%Versus best verified row

Best verified: Claude Opus 5 · 80.6%

Gap8.1 behindWeightDisplay only
HLE w/ toolsHumanity's Last Exam with toolsScore56.2%Versus best verified row

Best verified: Claude Opus 5.5 · 67.7%

Gap11.5 behindWeightDisplay only
CoWorkBenchScore74.8%Versus best verified row

Best verified: Qwen3.8-Omni-Flash · 75.3%

Gap0.5 behindWeightDisplay only
skillsBenchScore70.2%Versus best verified row

Best verified: Qwen3.8 Max · 70.2%

GapBest verifiedWeightDisplay only
WideResearchScore81.9%Versus best verified row

Best verified: Hy4 preview · 83.9%

Gap2 behindWeightDisplay only
WebArena-VerifiedWebArena-Verified Browser Agent BenchmarkScore66.8%Versus best verified row

Best verified: Muse Spark 1.1 · 69%

Gap2.2 behindWeightDisplay only
AndroidWorldScore85.3%Versus best verified row

Best verified: Qwen3.8-Omni-Flash · 87.1%

Gap1.8 behindWeightDisplay only
MobileWorldScore77.8%Versus best verified row

Best verified: Qwen3.8 Max · 77.8%

GapBest verifiedWeightDisplay only
Reasoning2 rows
Reasoning benchmark values, best verified comparison, weight, and source status
LongBench v2Score66.3%Versus best verified row

Best verified: Qwen3.8 Max · 66.3%

GapBest verifiedWeightWeighted 25%
MRCRv2Score92.9%Versus best verified row

Best verified: Sakana Fugu-Ultra · 93.6%

Gap0.7 behindWeightWeighted 20%
Multimodal24 rows
Multimodal benchmark values, best verified comparison, weight, and source status
MMMU-ProMassive Multi-discipline Multimodal Understanding ProScore82.3%Versus best verified row

Best verified: Gemini 3.5 Flash · 83.6%

Gap1.3 behindWeightWeighted 40%
CharXivCharXiv ReasoningScore93.5%Versus best verified row

Best verified: Qwen3.8 Max · 93.5%

GapBest verifiedWeightWeighted 20%
MathVisionScore95.2%Versus best verified row

Best verified: Qwen3.8 Max · 95.2%

GapBest verifiedWeightDisplay only
MathVision w/ PythonMathVision with PythonScore97.7%Versus best verified row

Best verified: Kimi K3 · 97.8%

Gap0.1 behindWeightDisplay only
BabyVisionScore82.0%Versus best verified row

Best verified: Qwen3.8 Max · 82.0%

GapBest verifiedWeightDisplay only
BabyVision w/ PythonBabyVision with PythonScore91.3%Versus best verified row

Best verified: Qwen3.8 Max · 91.3%

GapBest verifiedWeightDisplay only
ZeroBenchScore24.0%Versus best verified row

Best verified: Muse Spark · 33.0%

Gap9 behindWeightDisplay only
ZeroBench w/ PythonZeroBench_main with PythonScore49.0%Versus best verified row

Best verified: Qwen3.8 Max · 49.0%

GapBest verifiedWeightDisplay only
MedXpertQA (MM)MedXpertQA MultimodalScore80.4%Versus best verified row

Best verified: Qwen3.8 Max · 80.4%

GapBest verifiedWeightDisplay only
ScreenSpot ProScore84.5%Versus best verified row

Best verified: GPT-6 Astra · 92.7%

Gap8.2 behindWeightDisplay only
Vision2WebScore69.0%Versus best verified row

Best verified: Qwen3.8 Max · 69.0%

GapBest verifiedWeightDisplay only
CharXiv w/o toolsCharXiv Reasoning without toolsScore88.4%Versus best verified row

Best verified: Claude Mythos 5 · 88.9%

Gap0.5 behindWeightDisplay only
OmniDocBench 1.5Score92.1%Versus best verified row

Best verified: Qwen3.8 Max · 92.1%

GapBest verifiedWeightDisplay only
OCRBench V2Score74.2%Versus best verified row

Best verified: Qwen3.8 Max · 74.2%

GapBest verifiedWeightDisplay only
CC-OCRScore79.6%Versus best verified row

Best verified: Qwen3.6-35B-A3B · 81.9%

Gap2.3 behindWeightDisplay only
RealWorldQAScore88.0%Versus best verified row

Best verified: Qwen3.8-Flash-Next · 88.5%

Gap0.5 behindWeightDisplay only
ERQAScore77.8%Versus best verified row

Best verified: Qwen3.8 Max · 77.8%

GapBest verifiedWeightDisplay only
SimpleVQAScore75.0%Versus best verified row

Best verified: Qwen3.7 Plus · 81.7%

Gap6.7 behindWeightDisplay only
PerceptionBenchPerceptionBench (Internal)Score63.5%Versus best verified row

Best verified: Qwen3.8 Max · 63.5%

GapBest verifiedWeightDisplay only
Video-MME (with subtitle)Video-MME with subtitleScore90.4%Versus best verified row

Best verified: Qwen3.8 Max · 90.4%

GapBest verifiedWeightDisplay only
VideoMMMUScore88.7%Versus best verified row

Best verified: Qwen3.8 Max · 88.7%

GapBest verifiedWeightDisplay only
MMVUMultimodal Multi-disciplinary Video UnderstandingScore82.4%Versus best verified row

Best verified: Qwen3.8 Max · 82.4%

GapBest verifiedWeightDisplay only
MLVU (M-Avg)MLVU mean averageScore90.8%Versus best verified row

Best verified: Qwen3.8 Max · 90.8%

GapBest verifiedWeightDisplay only
LVBenchScore81.8%Versus best verified row

Best verified: Gemini 4 Argon · 91.7%

Gap9.9 behindWeightDisplay only
Knowledge6 rows
Knowledge benchmark values, best verified comparison, weight, and source status
HLEHumanity's Last ExamScore43.6%Versus best verified row

Best verified: Claude Fable 5.1 · 65%

Gap21.4 behindWeight44% ref. weight
MMLU-Pro (Vals)MMLU-Pro, Vals AI runScore88.6%Versus best verified row

Best verified: Claude Fable 5.1 · 92.4%

Gap3.8 behindWeight6% ref. weight
GPQAGraduate-Level Google-Proof Q&AScore92.6%Versus best verified row

Best verified: GPT-6 Astra · 96%

Gap3.4 behindWeight3% ref. weight
GPQA Diamond (Vals)GPQA Diamond, Vals AI runScore93.7%Versus best verified row

Best verified: Gemini 3.1 Pro · 95.5%

Gap1.8 behindWeight2% ref. weight
HLE w/o toolsHumanity's Last Exam without toolsScore43.6%Versus best verified row

Best verified: Claude Opus 5.5 · 64.4%

Gap20.8 behindWeightDisplay only
GPQA-DGPQA DiamondScore92.6%Versus best verified row

Best verified: GPT-6 Astra · 96.0%

Gap3.4 behindWeightDisplay only
Inst. Following1 row
Inst. Following benchmark values, best verified comparison, weight, and source status
IFBenchInstruction Following BenchmarkScore82.8%Versus best verified row

Best verified: MAI-Thinking-1 · 85%

Gap2.2 behindWeightWeighted 70%

Bars run 0–100; the dark tick marks the best source-verified value

All 60 rows

Lineage

The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.

  1. May 16, 2026

    Qwen3.7 Max

    Score 63.4 · Price not listed

  2. Jul 19, 2026

    Qwen3.8 Max Preview

    Not publicly ranked · Price not listed

  3. Aug 3, 2026 · you are here

    Qwen3.8 Max

    Score 72.1 · Price not listed

Radar

Qwen3.8 Max release history

Full release history

Radar confirmed these at the source. Use Qwen3.8 Max in your work? Explore Radar to follow supported changes and choose your alerts.

Radar

Spec sheet

Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.

API model ID
qwen3.8-maxAlibaba Cloud Model Studio pricing
Maximum output
Not sourced yet
Knowledge cutoff
Not sourced yet
Input modalities
Not sourced yet
Output modalities
Not sourced yet
Parameters
Not sourced yet
Availability
Open-weight Qwen3.8-2.4T-A95B and FP8 checkpoints are available from Qwen on Hugging Face for self-hosting. The hosted qwen3.8-max SKU remains available through QwenCloud with low, medium, and xhigh reasoning effort.
Cloud regions
Not tracked yet
Lifecycle
Current
API capabilities
Tool calling, structured outputs, and batch support are not tracked yet
Prompt caching
Not documented in the pricing recordAlibaba Cloud Model Studio pricing
Self-host
Open weights available; hardware estimate not sourced
Rate limits
Not tracked yet

How to read this profile

The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.

Qwen3.8 Max ranks #16 of 211 on the public leaderboard with a score of 72.1/100. Its source-verified position is #9 of 74.

Qwen3.8 Max is a open weight model with a 1M context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.

Open-weight Qwen3.8-2.4T-A95B and FP8 checkpoints are available from Qwen on Hugging Face for self-hosting. The hosted qwen3.8-max SKU remains available through QwenCloud with low, medium, and xhigh reasoning effort.

Official exact-value snapshot from Qwen's August 3, 2026 Qwen3.8-Max release post, preserving the benchmark-specific harnesses, tool settings, and paired metrics documented in the source. We keep Terminal-Bench 2.1 separate from the weighted Terminal-Bench 2.0 lane, split without-tool and tool-assisted rows where the schema supports both, and leave provider-run or internal evaluations display-only. QwenSWEBench, QwenQoderBench, QwenSVGBench, WorkSpaceBench, HealthBench, PLawBench, PRBench, and other unsupported launch rows remain outside the scored fields rather than being forced into non-equivalent keys. Qwen publishes the 2.4T-total-parameter, 95B-active text checkpoint with a 1,000,000-token context window under the custom Qwen3.8-Max License.

Qwen3.8 Max sits in the Qwen3.8 Max family with Qwen3.8 Max Preview. Its explicit predecessor is Qwen3.8 Max Preview. 60 of 496 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.

Its strongest eligible category is Multimodal & Grounded at #5, while its lowest eligible position is Coding at #30. particularly strong for screenshots, documents, charts, and grounded multimodal workflows.

Last updated September 30, 2026. Runtime fields remain blank until a sourced snapshot exists.

Deployment options

Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.

Published weights are available, but BenchLM does not yet have a sourced parameter and VRAM profile for this exact model. Hardware cost estimates stay unavailable until that sizing record is complete.

Estimate VRAM from known parameters

Questions

How does Qwen3.8 Max perform overall in AI benchmarks?

Qwen3.8 Max ranks #16 out of 211 models on the public BenchAlign leaderboard, with a score of 72.1/100. Its evidence status is Supported, and this profile shows 60 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.

Is Qwen3.8 Max good for knowledge and understanding?

Qwen3.8 Max ranks #23 out of 170 eligible models for knowledge and understanding, with a public category score of 66.1/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Qwen3.8 Max good for coding and programming?

Qwen3.8 Max ranks #30 out of 144 eligible models for coding and programming, with a public category score of 55.4/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Qwen3.8 Max good for reasoning and logic?

Qwen3.8 Max has source-displayable benchmark coverage for reasoning and logic, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Is Qwen3.8 Max good for agentic tool use and computer tasks?

Qwen3.8 Max ranks #14 out of 119 eligible models for agentic tool use and computer tasks, with a public category score of 65.4/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Qwen3.8 Max good for multimodal and grounded tasks?

Qwen3.8 Max ranks #5 out of 49 eligible models for multimodal and grounded tasks, with a public category score of 88.4/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Qwen3.8 Max good for instruction following?

Qwen3.8 Max ranks #16 out of 124 eligible models for instruction following, with a public category score of 90.5/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Qwen3.8 Max open source?

Qwen3.8 Max is an open-weight model from Alibaba. Its weights can be downloaded for local or hosted deployment, subject to the published license. Open weight does not automatically mean open source: training data and training code may remain private, and commercial restrictions can still apply.

Which sibling models are related to Qwen3.8 Max?

Qwen3.8 Max belongs to the Qwen3.8 Max family. Related tracked variants include Qwen3.8 Max Preview. A sibling link indicates shared lineage or a documented configuration relationship; it does not mean the variants have identical pricing, context limits, benchmark evidence, or deployment behavior. Compare before switching.

Does Qwen3.8 Max have full benchmark coverage on BenchLM?

No. Qwen3.8 Max currently has 61 source-displayable rows across 496 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.

What is the context window size of Qwen3.8 Max?

Qwen3.8 Max has a documented context window of 1M. That figure is the maximum combined prompt and retained-conversation space reported for this exact model; it is not the maximum output length. The profile keeps output limits separate because providers often publish those limits independently.

Compare Qwen3.8 Max with every tracked model636 comparisons