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BenchLM

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

CurrentProprietaryReasoning

Released Jun 3, 20261M context

Qwen3.7 Plus

Decision readingQwen3.7 Plus scores 56.5 out of 100 and ranks #59 of 211. This profile shows 52 source-displayable benchmark rows; its strongest eligible category is Multilingual at #3. No comparable first-party API price is published in the catalog.

Released Jun 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

56.5/100

field median 52.4#59 of 211 ranked models

Public

#59of 211

Verified #31 of 74

Price

Not listed

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

Speed

56tok/s

field median 89 tok/sFirst token 37.72 s

Context

1Mtokens

field median 256,000Reported for this model; direct source link not stored

Strongest published evidence

Multilingual ranks #3. A well-rounded choice across a range of tasks.

Validate before choosing

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

Source-linked · 52 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 #69 of 119Percentile 42ndWeight 22%11 benchmarksVerified
35.2
CodingRank #58 of 144Percentile 60thWeight 20%7 benchmarksVerified
42.8
ReasoningRank Not rankedWeight 17%2 benchmarksVerified
75.2
MultimodalRank #18 of 49Percentile 65thWeight 12%15 benchmarksVerified
73.5
KnowledgeRank #58 of 170Percentile 66thWeight 12%7 benchmarksVerified
52.6
MultilingualRank #3 of 16Percentile 87thWeight 7%5 benchmarksVerified
95.7
Inst. FollowingRank #18 of 124Percentile 86thWeight 5%2 benchmarksVerified
89.2
MathRank Not rankedWeight 5%3 benchmarksVerified
78.2

52 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. Agentic11/11 verified
  2. Coding7/7 verified
  3. Reasoning2/2 verified
  4. Multimodal15/15 verified
  5. Knowledge7/7 verified
  6. Multilingual5/5 verified
  7. Inst. Following2/2 verified
  8. Math3/3 verified
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.

Qwen3.7 Plus category percentile values

  • Agentic42nd percentile
  • Coding60th percentile
  • ReasoningNot eligible
  • Multimodal65th percentile
  • Knowledge66th percentile
  • Multilingual87th percentile
  • Instruction following86th percentile
  • MathNot eligible

The dashed outline is median of 6 nearest peers.

Eligible category ranks

  1. Agentic#69/119
  2. Coding#58/144
  3. ReasoningNot ranked
  4. Multimodal#18/49
  5. Knowledge#58/170
  6. Multilingual#3/16
  7. Inst. Following#18/124
  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.

Coding7 rows
Coding benchmark values, best verified comparison, weight, and source status
SWE-bench ProScore57.6%Versus best verified row

Best verified: Claude Opus 5.5 · 89.9%

Gap32.3 behindWeight26% ref. weight
SciCodeScientific Code BenchmarkScore51.3%Versus best verified row

Best verified: Sakana Fugu · 60.1%

Gap8.8 behindWeight10% ref. weight
SWE MultilingualScore75.8%Versus best verified row

Best verified: Claude Opus 5.5 · 93.9%

Gap18.1 behindWeight5% ref. weight
Terminal-Bench 2.0Score70.3%Versus best verified row

Best verified: GPT-5.5 · 82.0%

Gap11.7 behindWeightScored in Agentic
SWE-bench VerifiedSoftware Engineering Benchmark VerifiedScore77.7%Versus best verified row

Best verified: Claude Opus 5 · 96%

Gap18.3 behindWeightDisplay only
NL2RepoScore41.1%Versus best verified row

Best verified: DeepSeek V4.1 Flash · 65.4%

Gap24.3 behindWeightDisplay only
LiveCodeBenchLiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for CodeScore89.6%Versus best verified row

Best verified: Qwen3.7 Max · 91.6%

Gap2 behindWeightDisplay only
Agentic11 rows
Agentic benchmark values, best verified comparison, weight, and source status
OSWorld 2.0Score2.8%Versus best verified row

Best verified: GPT-6 Astra · 72.6%

Gap69.8 behindWeight10% ref. weight
Benchmark exact
Terminal-Bench 2.0Score70.3%Versus best verified row

Best verified: GPT-5.5 · 82%

Gap11.7 behindWeight6% ref. weight
OSWorld-VerifiedScore73.3%Versus best verified row

Best verified: Qwen3.8 Max · 86.1%

Gap12.8 behindWeight6% ref. weight
MCP AtlasScore73.2%Versus best verified row

Best verified: Muse Spark 1.1 · 88.1%

Gap14.9 behindWeight4% ref. weight
Terminal-Bench 2.1 (Vals)Terminal-Bench 2.1, Vals AI runScore52.8%Versus best verified row

Best verified: GPT-6 Astra · 87.3%

Gap34.5 behindWeight3% ref. weight
BFCL v4Berkeley Function Calling Leaderboard v4Score72.9%Versus best verified row

Best verified: BTL-3 · 88.5%

Gap15.6 behindWeight3% ref. weight
QwenClawBenchScore61.8%Versus best verified row

Best verified: Qwen3.7 Max · 64.3%

Gap2.5 behindWeightDisplay only
Claw-EvalScore62.7%Versus best verified row

Best verified: Ornith-1.5-397B · 81.4%

Gap18.7 behindWeightDisplay only
VITA-BenchScore45.6%Versus best verified row

Best verified: Qwen3.7 Max · 47.9%

Gap2.3 behindWeightDisplay only
DeepPlanningScore62.3%Versus best verified row

Best verified: Qwen3.7 Plus · 62.3%

GapBest verifiedWeightDisplay only
AndroidWorldScore81.0%Versus best verified row

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

Gap6.1 behindWeightDisplay only
Reasoning2 rows
Reasoning benchmark values, best verified comparison, weight, and source status
MRCRv2Score91.7%Versus best verified row

Best verified: Sakana Fugu-Ultra · 93.6%

Gap1.9 behindWeightWeighted 20%
CritPtCritical Physics TasksScore9.1%Versus best verified row

Best verified: GPT-6 Astra · 31.7%

Gap22.6 behindWeightFeeds overall
Multimodal15 rows
Multimodal benchmark values, best verified comparison, weight, and source status
MMMU-ProMassive Multi-discipline Multimodal Understanding ProScore79%Versus best verified row

Best verified: Gemini 3.5 Flash · 83.6%

Gap4.6 behindWeightWeighted 40%
CharXivCharXiv ReasoningScore85.9%Versus best verified row

Best verified: Qwen3.8 Max · 93.5%

Gap7.6 behindWeightWeighted 20%
MathVisionScore90.3%Versus best verified row

Best verified: Qwen3.8 Max · 95.2%

Gap4.9 behindWeightDisplay only
ERQAScore69.8%Versus best verified row

Best verified: Qwen3.8 Max · 77.8%

Gap8 behindWeightDisplay only
MedXpertQA (MM)MedXpertQA MultimodalScore71.0%Versus best verified row

Best verified: Qwen3.8 Max · 80.4%

Gap9.4 behindWeightDisplay only
ScreenSpot ProScore79.0%Versus best verified row

Best verified: GPT-6 Astra · 92.7%

Gap13.7 behindWeightDisplay only
SimpleVQAScore81.7%Versus best verified row

Best verified: Qwen3.7 Plus · 81.7%

GapBest verifiedWeightDisplay only
MMSearch-PlusScore41.4%Versus best verified row

Best verified: Qwen3.7 Plus · 41.4%

GapBest verifiedWeightDisplay only
RealWorldQAScore86.9%Versus best verified row

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

Gap1.6 behindWeightDisplay only
OmniDocBench 1.5Score91.4%Versus best verified row

Best verified: Qwen3.8 Max · 92.1%

Gap0.7 behindWeightDisplay only
OCRBench V2Score70.7%Versus best verified row

Best verified: Qwen3.8 Max · 74.2%

Gap3.5 behindWeightDisplay only
ODINW13Score51.1%Versus best verified row

Best verified: Qwen3.7 Plus · 51.1%

GapBest verifiedWeightDisplay only
Video-MME (with subtitle)Video-MME with subtitleScore88.0%Versus best verified row

Best verified: Qwen3.8 Max · 90.4%

Gap2.4 behindWeightDisplay only
VideoMMMUScore85.4%Versus best verified row

Best verified: Qwen3.8 Max · 88.7%

Gap3.3 behindWeightDisplay only
MLVU (M-Avg)MLVU mean averageScore87.4%Versus best verified row

Best verified: Qwen3.8 Max · 90.8%

Gap3.4 behindWeightDisplay only
Knowledge7 rows
Knowledge benchmark values, best verified comparison, weight, and source status
HLEHumanity's Last ExamScore34.7%Versus best verified row

Best verified: Claude Fable 5.1 · 65%

Gap30.3 behindWeight44% ref. weight
MMLU-ProMassive Multitask Language Understanding ProfessionalScore88.5%Versus best verified row

Best verified: Qwen3.7 Max · 89.6%

Gap1.1 behindWeight6% ref. weight
GPQAGraduate-Level Google-Proof Q&AScore90.3%Versus best verified row

Best verified: GPT-6 Astra · 96%

Gap5.7 behindWeight3% ref. weight
SuperGPQASuperGPQA: Scaling LLM Evaluation Across 285 Graduate DisciplinesScore71.4%Versus best verified row

Best verified: Qwen 3.6 Max (preview) · 73.9%

Gap2.5 behindWeight2% ref. weight
GPQA-DGPQA DiamondScore90.3%Versus best verified row

Best verified: GPT-6 Astra · 96.0%

Gap5.7 behindWeightDisplay only
MMLU-ReduxScore94.5%Versus best verified row

Best verified: Qwen3.7 Max · 95%

Gap0.5 behindWeightDisplay only
MMMLUScore89.0%Versus best verified row

Best verified: Interfaze Beta · 90.9%

Gap1.9 behindWeightDisplay only
Multilingual5 rows
Multilingual benchmark values, best verified comparison, weight, and source status
MMLU-ProXScore85.4%Versus best verified row

Best verified: Qwen3.7 Max · 87%

Gap1.6 behindWeightWeighted 100%
NOVA-63Score58.8%Versus best verified row

Best verified: Qwen3.5 397B · 59.1%

Gap0.3 behindWeightDisplay only
INCLUDEScore83.0%Versus best verified row

Best verified: Claude Opus 5 · 89.8%

Gap6.8 behindWeightDisplay only
MAXIFEScore88.8%Versus best verified row

Best verified: Qwen3.7 Max · 89.2%

Gap0.4 behindWeightDisplay only
PolyMathScore84.0%Versus best verified row

Best verified: Qwen3.7 Max · 86.5%

Gap2.5 behindWeightDisplay only
Inst. Following2 rows
Inst. Following benchmark values, best verified comparison, weight, and source status
IFBenchInstruction Following BenchmarkScore79.1%Versus best verified row

Best verified: MAI-Thinking-1 · 85%

Gap5.9 behindWeightWeighted 70%
IFEvalInstruction-Following EvalScore94.6%Versus best verified row

Best verified: Qwen3.5-27B · 95%

Gap0.4 behindWeightDisplay only
Math3 rows
Math benchmark values, best verified comparison, weight, and source status
HMMT Feb 2026Harvard-MIT Mathematics Tournament February 2026Score92.9%Versus best verified row

Best verified: Qwen3.7 Max · 97.1%

Gap4.2 behindWeightWeighted 25%
IMOAnswerBenchScore86.0%Versus best verified row

Best verified: dots3-note Preview · 90.9%

Gap4.9 behindWeightDisplay only
ApexScore22.7%Versus best verified row

Best verified: Hy4 preview · 74.2%

Gap51.5 behindWeightDisplay only

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

All 52 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. Apr 2, 2026

    Qwen3.6 Plus

    Score 55.2 · Price not listed

  2. Jun 3, 2026 · you are here

    Qwen3.7 Plus

    Score 56.5 · Price not listed

Base entry

Radar

Qwen3.7 Plus release history

Full release history

Radar confirmed these at the source. Use Qwen3.7 Plus 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
Not published
Context window
1M
Maximum output
Not sourced yet
Knowledge cutoff
Not sourced yet
Input modalities
Not sourced yet
Output modalities
Not sourced yet
Parameters
Not disclosed by the provider
Availability
Not sourced yet
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 record
Self-host
Weights are not published
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.

Qwen3.7 Plus ranks #59 of 211 on the public leaderboard with a score of 56.54/100. Its source-verified position is #31 of 74.

Qwen3.7 Plus is a proprietary model with a 1M context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.

Official exact-value snapshot from Alibaba Cloud's June 3, 2026 Qwen3.7-Plus launch article and Model Studio API examples. BenchLM maps directly comparable table rows and leaves provider-specific rows such as CoWorkBench, SkillsBench, MCP-Mark, SpreadsheetBench-v1, KernelBench L3, QwenWorldBench, QwenVision2Code, QwenSVG, WorldVQA, BabyVision, BC-VL, MMBC, LingoQA, Ego3D-Bench, SURDS, VLADBench, TVBench, LVBench, and CountQA outside the current schema.

Its explicit predecessor is Qwen3.6 Plus. 52 of 496 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.

Its strongest eligible category is Multilingual at #3, while its lowest eligible position is Agentic at #69. a well-rounded choice across a range of tasks.

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

Questions

How does Qwen3.7 Plus perform overall in AI benchmarks?

Qwen3.7 Plus ranks #59 out of 211 models on the public BenchAlign leaderboard, with a score of 56.54/100. Its evidence status is Supported, and this profile shows 52 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.

Is Qwen3.7 Plus good for knowledge and understanding?

Qwen3.7 Plus ranks #58 out of 170 eligible models for knowledge and understanding, with a public category score of 52.6/100. 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 Qwen3.7 Plus good for coding and programming?

Qwen3.7 Plus ranks #58 out of 144 eligible models for coding and programming, with a public category score of 42.8/100. 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 Qwen3.7 Plus good for mathematics?

Qwen3.7 Plus has source-displayable benchmark coverage for mathematics, 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 Qwen3.7 Plus good for reasoning and logic?

Qwen3.7 Plus 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 Qwen3.7 Plus good for agentic tool use and computer tasks?

Qwen3.7 Plus ranks #69 out of 119 eligible models for agentic tool use and computer tasks, with a public category score of 35.2/100. 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 Qwen3.7 Plus good for multimodal and grounded tasks?

Qwen3.7 Plus ranks #18 out of 49 eligible models for multimodal and grounded tasks, with a public category score of 73.5/100. 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 Qwen3.7 Plus good for instruction following?

Qwen3.7 Plus ranks #18 out of 124 eligible models for instruction following, with a public category score of 89.2/100. 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 Qwen3.7 Plus good for multilingual tasks?

Qwen3.7 Plus ranks #3 out of 16 eligible models for multilingual tasks, with a public category score of 95.7/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.

Does Qwen3.7 Plus have full benchmark coverage on BenchLM?

No. Qwen3.7 Plus currently has 70 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 Qwen3.7 Plus?

Qwen3.7 Plus has a reported context window of 1M in the exact-model catalog record. The value stays visible, but the profile marks its source link as unavailable instead of presenting it as directly documented. Maximum output length remains separate because providers often publish a different limit.

Compare Qwen3.7 Plus with every tracked model636 comparisons