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Gemini 3.7 Flash vs Qwen3.6 Max

Full profiles: Gemini 3.7 Flash (Google) and Qwen3.6 Max (Alibaba): every benchmark, price and rank.

Updated · Data from 9 sources

As of 2 Nov 2026, Gemini 3.7 Flash and Qwen3.6 Max are neck and neck on quality (62.2 vs 62.4 on the BenchLeader Index, inside the ±4.7 margin), and Gemini 3.7 Flash is 1.9× cheaper at $1.50 vs $2.92 per 1M tokens blended. Choose Gemini 3.7 Flash for coding (63 vs 56), knowledge (66 vs 60), and reasoning (68 vs 63); choose Qwen3.6 Max for agents & tools (72 vs 48) and maths (65 vs 63).

Key facts (as of 2 Nov 2026)

  • Gemini 3.7 Flash scores 62.2 on the BenchLeader Index and Qwen3.6 Max scores 62.4 (BenchLeader, 2 Nov 2026).
  • Gemini 3.7 Flash costs $1.50 per 1M tokens blended (list price, 2 Nov 2026).
  • Qwen3.6 Max costs $2.92 per 1M tokens blended (list price, 2 Nov 2026).
  • Of the 19 benchmarks both models have, Gemini 3.7 Flash leads 19 (BenchLeader, 2 Nov 2026).
  • On Arena WebDev, Gemini 3.7 Flash is rated 1590 and Qwen3.6 Max 1482 (LMArena, as published by 2 Nov 2026).
Gemini 3.7 Flash benchmarks high Google Qwen3.6 Max benchmarks max AlibabaAdd a third model

Which to pick for…

The pick's numbers come first. Category scores on the BenchLeader scale (50 is the average model, 15 points one standard deviation). High confidence means a lead of half a standard deviation or more; under one point is called either.

Use casePickWhyConfidence
CodingGemini 3.7 Flash63 vs 56 category score; Arena WebDev 1590 vs 1482Medium
Agents & tool useQwen3.6 Max72 vs 48 category scoreHigh
MathsQwen3.6 Max65 vs 63 category score; Arena Maths 1476 vs 1503Medium
ReasoningGemini 3.7 Flash68 vs 63 category score; GPQA Diamond 94.8% vs 87.4%Medium
KnowledgeGemini 3.7 Flash66 vs 60 category score; SimpleQA Verified 69.2% vs 52.0%Medium
Long documentsEither66 vs 65 category score; AA-LCR v1.1 81.7% vs 80.7%Either
Chat quality (human preference)Gemini 3.7 Flash68 vs 65 on Arena votesMedium
Lowest costGemini 3.7 Flash$1.50 vs $2.96 per 1M blended; agentic coding session $0.060 vs $0.111–
High volume on a budgetNeither flagshipA smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs–

Key differences

  • Gemini 3.7 Flash (high) and Qwen3.6 Max (max) are neck and neck on quality (62.2 vs 62.4, within the ±4.7 margin).
  • Gemini 3.7 Flash (high) is stronger in coding, human preference, knowledge, long context, multimodal, reasoning.
  • Qwen3.6 Max (max) is stronger in agents & tools, maths, instruction following.
  • Gemini 3.7 Flash (high) is 2.0× cheaper ($1.50 vs $2.96 per 1M blended).

At a glance

SpecGemini 3.7 FlashQwen3.6 Max
DeveloperGoogleAlibaba
Released13 Aug 202620 Apr 2026
Context window (tokens)1,048,576245,800
Compared atGemini 3.7 Flash (high)Qwen3.6 Max (max)
Open weightsNoNo
Price in / out / cached input per 1M$0.750 / $3.75 / $0.075$1.32 / $7.90 / $0.132

Category by category

Category scores on the BenchLeader scale: 50 is the average evaluated model, 15 points is one standard deviation. A gap under one point is called level.

CategoryGemini 3.7 Flash (high)Qwen3.6 Max (max)Leader
Reasoning68.362.7Gemini 3.7 Flash
Coding62.756.3Gemini 3.7 Flash
Agents & tools47.772.1Qwen3.6 Max
Maths63.064.7Qwen3.6 Max
Knowledge66.260.0Gemini 3.7 Flash
Instruction following–74.6not comparable
Human preference68.264.6Gemini 3.7 Flash
Multimodal67.3–not comparable
Long context65.765.2level

On one chart

Each domain on the index's own scale, where 50 is an average model. Click a domain to see the benchmarks behind it. Pick up to 5 models from the list.

2550 avg75ReasoningCodingAgents & toolsMathsKnowledgeLong contextHumanpreferenceGemini 3.7 Flash, Reasoning: 68.3Gemini 3.7 Flash, Coding: 62.7Gemini 3.7 Flash, Agents & tools: 47.7Gemini 3.7 Flash, Maths: 63.0Gemini 3.7 Flash, Knowledge: 66.2Gemini 3.7 Flash, Long context: 65.7Gemini 3.7 Flash, Human preference: 68.2Qwen3.6 Max, Reasoning: 62.7Qwen3.6 Max, Coding: 56.3Qwen3.6 Max, Agents & tools: 72.1Qwen3.6 Max, Maths: 64.7Qwen3.6 Max, Knowledge: 60.0Qwen3.6 Max, Long context: 65.2Qwen3.6 Max, Human preference: 64.6

Not drawn, measured for fewer than two of these models: Instruction following, Multimodal.

ModelIndex

Where sources disagree

Across the 19 benchmarks both have, Gemini 3.7 Flash leads 19, Qwen3.6 Max leads 0. Every overall index that rates both puts Gemini 3.7 Flash ahead.

Overall indexGemini 3.7 Flash (high)Qwen3.6 Max (max)Leader
BenchLeader Index62.262.4neck and neck
Arena Text14901460Gemini 3.7 Flash

Each publisher runs its own tasks, harnesses and effort settings, so their overall verdicts can differ; BenchLeader reconciles them on one scale. † measured at another effort setting of the same model (the publisher did not test the one compared here).

Price, speed and latency

List prices blended at three input tokens per output token. Per-task prices use the token counts on the methodology page. Cost, tokens and time per benchmark task are measured: Artificial Analysis’ averages over its whole Intelligence Index run.

MeasureGemini 3.7 Flash (high)Qwen3.6 Max (max)
Blended price per 1M tokens$1.50$2.96
Input / output per 1M$0.750 / $3.75$1.32 / $7.90
Cached input per 1M$0.075$0.132
Price per task: chat reply$0.0014$0.0029
Price per task: summarize a 30-page report$0.011$0.021
Price per task: code edit$0.010$0.020
Price per task: agentic coding session$0.060$0.111
Price per task: structured extraction$0.0023$0.0042
Agentic coding session, input mostly cached$0.030$0.057
Output speed91 tok/s–
Time to first answer2.4 s–

Each model is compared at its best-ranked reasoning-effort setting. Gemini 3.7 Flash (high) scores 62.2 and takes 2 s to its first answer token; Gemini 3.7 Flash (medium) scores 60.3 in 2 s, Gemini 3.7 Flash (low) scores 57.5 in 2 s. Qwen3.6 Max (max) scores 62.4. Higher effort means more thinking before the answer: better scores, longer waits and more tokens billed. How reasoning effort changes scores and cost.

Every benchmark

94 benchmarks, grouped by category; each name links to the board and its leaders. † measured at another effort setting of the same model, shown for reference and not counted as a win.

MetricPublisherGemini 3.7 Flash (high)Qwen3.6 Max (max)
BenchLeader IndexBenchLeader62.262.4
Agents & tools scoreBenchLeader47.772.1
Coding scoreBenchLeader62.756.3
Human preference scoreBenchLeader68.264.6
Knowledge scoreBenchLeader66.260.0
Long context scoreBenchLeader65.765.2
Maths scoreBenchLeader63.064.7
Multimodal scoreBenchLeader67.3–
Reasoning scoreBenchLeader68.362.7
Instruction following scoreBenchLeader–74.6
Blended price $/MBenchLeader$1.50$2.96
Output speedBenchLeader91 tok/s–
Time to first answerBenchLeader2.4 s–
Context windowBenchLeader1,048,576 tokens245,800 tokens
Reasoning
GPQA DiamondEpoch AI Benchmarking Hub94.8%87.4%
SimpleBenchSimpleBench–63.0%
Arena Hard PromptsArena (LMArena)15091482
LiveBench 1.0 ReasoningLiveBench87.8%–
GPQA Diamond (AA)Artificial Analysis94.5%88.8%
Humanity's Last Exam (AA)Artificial Analysis47.9%30.8%
GPQA Diamond (Vals)Vals AI93.9%–
ARC-AGI-1ARC Prize95.5%–
ARC-AGI-2ARC Prize84.6%–
CritPtArtificial Analysis14.3%3.7%
Chess PuzzlesEpoch AI Benchmarking Hub66.0%–
Mystery Game PuzzlesEpoch AI Benchmarking Hub37.0%19.0%†
LMCAEpoch AI Benchmarking Hub50.4%42.5%
DTBenchEpoch AI Benchmarking Hub96.8%87.2%
ForecastBenchForecastBench66.2%–
Coding
SWE-bench Verified (Epoch)Epoch AI Benchmarking Hub–76.7%
SciCodeSciCode57.2%–
FrontierCodeCognition43.6%†–
Arena CodingArena (LMArena)15201511
Arena WebDevArena (LMArena)15901482
LiveBench 1.0 CodingLiveBench78.9%–
LiveCodeBenchVals AI88.7%–
IOIVals AI67.8%–
SWE-bench (Vals)Vals AI80.8%72.8%
Code MigrationVals AI34.8%–
Show all 94 benchmarks
MetricPublisherGemini 3.7 Flash (high)Qwen3.6 Max (max)
Coding
ProgramBenchVals AI0.0%–
Vibe Code Bench v1.1Vals AI70.4%–
MirrorCodeEpoch AI Benchmarking Hub41.1%–
DeepSWE v1.1Epoch AI Benchmarking Hub65.3%–
ALE-BenchEpoch AI Benchmarking Hub904.3–
FrontierSWEEpoch AI Benchmarking Hub20.3%–
Terminal-Bench 4.0 (AA)Artificial Analysis13.6%–
Terminal-Bench 2.1 (AA)Artificial Analysis85.8%–
Agents & tools
Terminal-BenchTerminal-Bench11.2%–
Remote Labor IndexScale AI / CAIS5.0%†–
APEX-AgentsMercor67.8%†–
Arena AgentArena (LMArena)-1.3–
LiveBench Agentic CodingLiveBench58.3%–
Terminal-Bench HardArtificial Analysis–43.9%
τ²-Bench Telecom (AA)Artificial Analysis–95.9%
Terminal-Bench 2.1 (Vals)Vals AI77.5%–
τ³-Banking (AA)Artificial Analysis32.8%–
Analyst Agent (AA)Artificial Analysis60.0%–
CyberBenchVals AI43.8%–
Finance Agent v2Vals AI59.0%–
Harvey's Legal Agent Benchmark v1Vals AI8.8%–
Legal Research BenchVals AI34.6%–
SkillsBenchVals AI65.9%–
SREBenchVals AI4.6%–
Tax Agent BenchVals AI22.8%–
Terminal-Bench 2.0 (Vals)Vals AI–51.7%
Terminal-Bench 4.0 (Vals)Vals AI12.1%–
Terminal-Bench ScienceVals AI7.1%–
Vending-Bench 2Andon Labs–4254.2
AutomationBenchArtificial Analysis62.0%–
GDP.pdf (AA)Artificial Analysis23.6%–
EnterpriseOps-GymArtificial Analysis50.4%†–
FACTS SearchGoogle80.9%†–
Maths
FrontierMath Tiers 1–3Epoch AI Benchmarking Hub71.6%–
FrontierMath Tier 4Epoch AI Benchmarking Hub36.6%–
OTIS Mock AIMEEpoch AI Benchmarking Hub97.2%91.1%
ProofBenchVals AI58.0%†–
LiveBench MathematicsLiveBench93.5%–
Arena MathsArena (LMArena)15031476
Knowledge
SimpleQA VerifiedEpoch AI Benchmarking Hub69.2%52.0%
LiveBench 1.0 Data AnalysisLiveBench68.0%–
MMLU-ProVals AI90.1%–
LegalBenchVals AI87.3%–
CorpFinVals AI–66.5%
TaxEvalVals AI74.7%–
CaseLaw v2Vals AI–47.9%
Excel Modeling BenchmarkVals AI71.3%–
MedCodeVals AI53.4%–
MedScribeVals AI83.9%–
GDP.pdfEpoch AI Benchmarking Hub23.8%–
Instruction following
LiveBench LanguageLiveBench85.5%–
LiveBench Instruction FollowingLiveBench79.9%–
IFBenchArtificial Analysis–76.6%
Arena Instruction FollowingArena (LMArena)14871451
Human preference
Arena TextArena (LMArena)14901460
Arena Creative WritingArena (LMArena)14901437
Arena Multi-turnArena (LMArena)14881467
Arena Longer QueriesArena (LMArena)15011473
Multimodal
Arena VisionArena (LMArena)1314–
MMMU-ProArtificial Analysis85.5%–
MMMU-Pro (Vals)Vals AI89.0%–
MortgageTaxVals AI66.7%–
Long context
AA-LCR v1.1Artificial Analysis81.7%80.7%
MLCRArtificial Analysis12.2%–
Composite
Epoch Capabilities IndexEpoch AI Benchmarking Hub158.2†149.4
LiveBench 1.0LiveBench78.8%–
AA Intelligence Index v4.3.2Artificial Analysis39.128.4
AA Progress Index v1Artificial Analysis317.4297.1
Vals RSI IndexVals AI18.3%–

Data as of 2026-11-02. Best configuration of each model; every score links to its source on the model pages.

What changed

  • Gemini 3.7 Flash (high): 1 new result (MirrorCode).
  • Gemini 3.7 Flash (high): 1 new result (AA Progress Index v1).
  • Qwen3.6 Max (max): 1 new result (AA Progress Index v1).
  • Gemini 3.7 Flash (high): 2 new results (Harvey's Legal Agent Benchmark v1, Vals RSI Index).
  • Gemini 3.7 Flash (high): input price moved from $0.38/M to $0.75/M (97% up); output price moved from $1.88/M to $3.75/M (99% up).
  • Qwen3.6 Max (max): BenchLeader Index 63.3 → 62.8.
  • Gemini 3.7 Flash (high): 1 score revision; input price moved from $0.75/M to $0.38/M (49% down); output price moved from $3.75/M to $1.88/M (50% down).
  • Gemini 3.7 Flash (high): 1 new result (ForecastBench).
  • Gemini 3.7 Flash (high): BenchLeader Index 60.8 → 62.6.
  • Gemini 3.7 Flash (high): 18 new results (AA Intelligence Index v4.3.2, GPQA Diamond (AA), Humanity's Last Exam (AA)…).

Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs

Gemini 3.7 Flash vs Qwen3.6 Max: questions

Is Gemini 3.7 Flash better than Qwen3.6 Max?
Gemini 3.7 Flash (high) and Qwen3.6 Max (max) are neck and neck on quality (62.2 vs 62.4, within the ±4.7 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 2 Nov 2026, so check the category scores for your use.
Gemini 3.7 Flash vs Qwen3.6 Max: which is cheaper, and will that change?
Gemini 3.7 Flash is cheaper today: $1.50 against $2.92 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
Is Gemini 3.7 Flash or Qwen3.6 Max better for coding?
Gemini 3.7 Flash scores higher in coding (63 vs 56 on the category index, where 50 is average). On Arena WebDev, the top shared coding benchmark, it is 1590 for Gemini 3.7 Flash against 1482 for Qwen3.6 Max.
Is Gemini 3.7 Flash or Qwen3.6 Max better for agents and tool use?
Qwen3.6 Max scores higher in agentic tasks (72 vs 48 on the category index, where 50 is average).
Which is better for long documents?
They are level on long-context benchmarks (66 vs 65). Gemini 3.7 Flash accepts more context: 1,048,576 against 245,800 tokens for Qwen3.6 Max.
More questions (2)
Do independent benchmarks agree on Gemini 3.7 Flash vs Qwen3.6 Max?
Across the 19 benchmarks both have, Gemini 3.7 Flash leads 19, Qwen3.6 Max leads 0. Every overall index that rates both puts Gemini 3.7 Flash ahead.
When was Gemini 3.7 Flash released?
Gemini 3.7 Flash was released on 13 Aug 2026.