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Gemini 3.7 Flash vs Qwen3.5 397B A17B

Gemini 3.7 Flash leads Qwen3.5 397B A17B on the Artificial Analysis Intelligence Index, 39.6 to 21.4, and Qwen3.5 397B A17B costs 1.6x less per output token ($2.34 vs $3.75 per million). Updated October 22, 2026; 60 benchmarks have a result for both.

Replace Gemini 3.7 Flash Replace Qwen3.5 397B A17B
Gemini 3.7 FlashGoogle
Coding
58.0
Overall
65.7
Output $/M
$3.75
60
Qwen3.5 397B A17BQwen
Coding
No data
Overall
57.1
Output $/M
$2.34
0
vs boards won of 60 shared

Gemini 3.7 Flash or Qwen3.5 397B A17B: which to pick

Only Gemini 3.7 Flash has a coding score, 58.0 on the Vibe Coding Index; Qwen3.5 397B A17B has none, so the two cannot be ranked on coding.

Pick Qwen3.5 397B A17B for output tokens 1.6x cheaper ($2.34 vs $3.75 per million).

Model AGemini 3.7 FlashGoogle58.0/1006 independent benchmarks$1.78 per solved taskModel BQwen3.5 397B A17BQwenNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
60
Gemini 3.7 Flash only
54
Qwen3.5 397B A17B only
5
Like-for-like categories
8 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
Gemini 3.7 Flash 58.0 from 6 benchmarks, Qwen3.5 397B A17B not benchmarked.
Widest category
Agentic work, 42.9 points apart on average over 1 shared benchmark.
Widest single gap
APEX-Agents: Gemini 3.7 Flash 67.8% against Qwen3.5 397B A17B 24.9%, 42.9 points apart on a 0 to 100 scale.
Output price
Gemini 3.7 Flash $3.75 against Qwen3.5 397B A17B $2.34 per million output tokens, 1.6x apart.
Context window
Gemini 3.7 Flash takes 1.05M tokens, Qwen3.5 397B A17B 262K.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryGemini 3.7 FlashBarsQwen3.5 397B A17BTies
Coding70
Intelligence20
Agentic work10
Reasoning90
Math40
Knowledge40
Web design70
General260
All shared boards600
CodingLike-for-likeSix of these boards feed the Vibe Coding Index70
Coding benchmarks for Gemini 3.7 Flash and Qwen3.5 397B A17B
BenchmarkGemini 3.7 FlashQwen3.5 397B A17BLeader
LiveBench coding80.5%Not measuredOnly Gemini 3.7 Flash measured
LMArena WebDev15911400Gemini 3.7 Flash
AA Coding Index71.5Not measuredOnly Gemini 3.7 Flash measured
LiveCodeBench (Vals AI)88.7%Not measuredOnly Gemini 3.7 Flash measured
SWE-bench Verified (Vals AI)80.8%Not measuredOnly Gemini 3.7 Flash measured
Terminal-Bench 4 (Vals AI)12.1%Not measuredOnly Gemini 3.7 Flash measured
Vibe Code Bench (Vals AI)70.4%Not measuredOnly Gemini 3.7 Flash measured
Code migration (Vals AI)34.8%Not measuredOnly Gemini 3.7 Flash measured
ProgramBench (Vals AI)0.0%Not measuredOnly Gemini 3.7 Flash measured
IOI (Vals AI)67.8%Not measuredOnly Gemini 3.7 Flash measured
Terminal-Bench 2.1 (Vals AI)77.5%Not measuredOnly Gemini 3.7 Flash measured
SkillsBench (Vals AI)65.9%Not measuredOnly Gemini 3.7 Flash measured
CyberBench (Vals AI)43.8%Not measuredOnly Gemini 3.7 Flash measured
SciCode59.8%44.8%Gemini 3.7 Flash
Terminal-Bench Hard (Artificial Analysis run)Not measured40.9%Only Qwen3.5 397B A17B measured
FrontierCode43.6%Not measuredOnly Gemini 3.7 Flash measured
FrontierSWE20.3%Not measuredOnly Gemini 3.7 Flash measured
ALE-Bench904.3621.9Gemini 3.7 Flash
LMArena Text: coding14991464Gemini 3.7 Flash
LMArena Text: software and IT14981463Gemini 3.7 Flash
LMArena WebDev: React15871388Gemini 3.7 Flash
LMArena WebDev: HTML15931410Gemini 3.7 Flash
LMArena WebDev: from an image1599Not measuredOnly Gemini 3.7 Flash measured
SciCode13.8%Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 15 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Gemini 3.7 Flash and Qwen3.5 397B A17B
BenchmarkGemini 3.7 FlashQwen3.5 397B A17BLeader
AA Intelligence Index39.621.4Gemini 3.7 Flash
Epoch Capabilities Index158.0146.8Gemini 3.7 Flash
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for Gemini 3.7 Flash and Qwen3.5 397B A17B
BenchmarkGemini 3.7 FlashQwen3.5 397B A17BLeader
Design Arena: agents building web apps1223Not measuredOnly Gemini 3.7 Flash measured
Design Arena: agents building full-stack apps1208Not measuredOnly Gemini 3.7 Flash measured
Design Arena: agents building mobile apps1229Not measuredOnly Gemini 3.7 Flash measured
Design Arena: agents building Android apps1243Not measuredOnly Gemini 3.7 Flash measured
Design Arena: agents building Godot games1264Not measuredOnly Gemini 3.7 Flash measured
Design Arena: agents building games1235Not measuredOnly Gemini 3.7 Flash measured
Design Arena: spreadsheets1058Not measuredOnly Gemini 3.7 Flash measured
LiveBench research76.5%Not measuredOnly Gemini 3.7 Flash measured
LiveBench browser56.0%Not measuredOnly Gemini 3.7 Flash measured
LiveBench long agentic28.3%Not measuredOnly Gemini 3.7 Flash measured
SREBench (Vals AI)4.6%Not measuredOnly Gemini 3.7 Flash measured
Finance Agent (Vals AI)59.0%Not measuredOnly Gemini 3.7 Flash measured
Tax Agent Bench (Vals AI)22.8%Not measuredOnly Gemini 3.7 Flash measured
Legal Research Bench (Vals AI)34.6%Not measuredOnly Gemini 3.7 Flash measured
Excel Modeling Benchmark (Vals AI)71.3%Not measuredOnly Gemini 3.7 Flash measured
Terminal-Bench-Science (Vals AI)7.1%Not measuredOnly Gemini 3.7 Flash measured
τ²-Bench TelecomNot measured95.6%Only Qwen3.5 397B A17B measured
APEX-Agents67.8%24.9%Gemini 3.7 Flash
Remote Labor Index5.0%Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 22 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index90
Reasoning benchmarks for Gemini 3.7 Flash and Qwen3.5 397B A17B
BenchmarkGemini 3.7 FlashQwen3.5 397B A17BLeader
GPQA Diamond93.9%Not measuredOnly Gemini 3.7 Flash measured
LiveBench reasoning87.8%Not measuredOnly Gemini 3.7 Flash measured
MMMU Pro (Vals AI)89.0%Not measuredOnly Gemini 3.7 Flash measured
GPQA Diamond (Artificial Analysis run)94.5%89.3%Gemini 3.7 Flash
Humanity's Last Exam (Artificial Analysis run)47.9%29.0%Gemini 3.7 Flash
GPQA Diamond (Epoch AI run)94.8%86.4%Gemini 3.7 Flash
ARC-AGI95.5%Not measuredOnly Gemini 3.7 Flash measured
ARC-AGI-284.6%Not measuredOnly Gemini 3.7 Flash measured
Chess puzzles66.0%Not measuredOnly Gemini 3.7 Flash measured
Mystery game puzzles37.0%18.0%Gemini 3.7 Flash
LMArena Text: hard prompts14951448Gemini 3.7 Flash
LMArena Text: expert15121462Gemini 3.7 Flash
LMArena Text: hard prompts in English14871450Gemini 3.7 Flash
LMArena Vision: diagrams13291277Gemini 3.7 Flash
LMArena Vision: homework13201292Gemini 3.7 Flash
Neither model has a result on the other 7 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index40
Math benchmarks for Gemini 3.7 Flash and Qwen3.5 397B A17B
BenchmarkGemini 3.7 FlashQwen3.5 397B A17BLeader
OTIS Mock AIME97.2%88.9%Gemini 3.7 Flash
FrontierMath, tiers 1 to 371.6%31.2%Gemini 3.7 Flash
FrontierMath, tier 436.6%Not measuredOnly Gemini 3.7 Flash measured
ProofBench58.0%Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: math15111453Gemini 3.7 Flash
LMArena Text: mathematical work15021454Gemini 3.7 Flash
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for Gemini 3.7 Flash and Qwen3.5 397B A17B
BenchmarkGemini 3.7 FlashQwen3.5 397B A17BLeader
MMLU Pro90.1%Not measuredOnly Gemini 3.7 Flash measured
LegalBench (Vals AI)87.3%Not measuredOnly Gemini 3.7 Flash measured
TaxEval (Vals AI)74.7%Not measuredOnly Gemini 3.7 Flash measured
MortgageTax (Vals AI)66.7%Not measuredOnly Gemini 3.7 Flash measured
MedCode (Vals AI)53.4%Not measuredOnly Gemini 3.7 Flash measured
SimpleQA Verified69.2%Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: science15111457Gemini 3.7 Flash
LMArena Text: medicine and healthcare14941455Gemini 3.7 Flash
LMArena Text: legal and government14961441Gemini 3.7 Flash
LMArena Text: business and finance14791435Gemini 3.7 Flash
FACTS Benchmark Suite71.2%Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index70
Web design benchmarks for Gemini 3.7 Flash and Qwen3.5 397B A17B
BenchmarkGemini 3.7 FlashQwen3.5 397B A17BLeader
Design Arena: websites13031190Gemini 3.7 Flash
Design Arena: UI components12961160Gemini 3.7 Flash
Design Arena: game dev13171140Gemini 3.7 Flash
Design Arena: data viz13151175Gemini 3.7 Flash
Design Arena: 3D13071160Gemini 3.7 Flash
Design Arena: all code categories13081179Gemini 3.7 Flash
Design Arena: SVG12831139Gemini 3.7 Flash
Design Arena: ASCII art1276Not measuredOnly Gemini 3.7 Flash measured
LiveBench design73.2%Not measuredOnly Gemini 3.7 Flash measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index260
General benchmarks for Gemini 3.7 Flash and Qwen3.5 397B A17B
BenchmarkGemini 3.7 FlashQwen3.5 397B A17BLeader
LiveBench data analysis68.0%Not measuredOnly Gemini 3.7 Flash measured
SAGE (Vals AI)49.2%Not measuredOnly Gemini 3.7 Flash measured
MedScribe (Vals AI)83.9%Not measuredOnly Gemini 3.7 Flash measured
IFBenchNot measured78.8%Only Qwen3.5 397B A17B measured
Long context reasoning (AA-LCR)83.0%77.3%Gemini 3.7 Flash
DTBench96.8%87.5%Gemini 3.7 Flash
LMCA50.4%37.9%Gemini 3.7 Flash
Furniture assembly26.7%Not measuredOnly Gemini 3.7 Flash measured
LMArena Text14891437Gemini 3.7 Flash
LMArena Text: instruction following14841424Gemini 3.7 Flash
LMArena Text: creative writing14881402Gemini 3.7 Flash
LMArena Vision13141262Gemini 3.7 Flash
LMArena Text: English14831443Gemini 3.7 Flash
LMArena Text: non-English14871430Gemini 3.7 Flash
LMArena Text: Chinese15521498Gemini 3.7 Flash
LMArena Text: German15061445Gemini 3.7 Flash
LMArena Text: Japanese15111429Gemini 3.7 Flash
LMArena Text: Korean14811384Gemini 3.7 Flash
LMArena Text: French15001462Gemini 3.7 Flash
LMArena Text: Spanish14951441Gemini 3.7 Flash
LMArena Text: Russian15151430Gemini 3.7 Flash
LMArena Text: Polish15031447Gemini 3.7 Flash
LMArena Text: multi-turn14851446Gemini 3.7 Flash
LMArena Text: longer queries14921441Gemini 3.7 Flash
LMArena Text: writing and language14911415Gemini 3.7 Flash
LMArena Text: entertainment and media14771399Gemini 3.7 Flash
LMArena Vision: English13091268Gemini 3.7 Flash
LMArena Vision: Chinese13941314Gemini 3.7 Flash
LMArena Vision: reading text13221271Gemini 3.7 Flash
LMArena Vision: humor12991262Gemini 3.7 Flash
LMArena Vision: captioningNot measured1230Only Qwen3.5 397B A17B measured
LMArena Vision: recognizing thingsNot measured1265Only Qwen3.5 397B A17B measured
LMArena Vision: creative writing13121260Gemini 3.7 Flash
Neither model has a result on the other 13 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemini 3.7 Flash and Qwen3.5 397B A17B
BenchmarkGemini 3.7 FlashQwen3.5 397B A17BLeader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

Gemini 3.7 Flash$0.0026Fits in one request
Qwen3.5 397B A17B$0.0016Fits in one request

Qwen3.5 397B A17B costs less

Repository review

50K input + 3K output tokens

Gemini 3.7 Flash$0.049Fits in one request
Qwen3.5 397B A17B$0.027Fits in one request

Qwen3.5 397B A17B costs less

Agent loop

200K input + 10K output tokens

Gemini 3.7 Flash$0.188Fits in one request
Qwen3.5 397B A17B$0.101Fits in one request

Qwen3.5 397B A17B costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of Gemini 3.7 Flash and Qwen3.5 397B A17B
SpecificationGoogle Gemini 3.7 FlashQwen3.5 397B A17B
MakerGoogleQwen
WeightsNo public weights listedOpen weights
ReleasedAugust 13, 2026February 16, 2026
Context window1.05M262K
Input $/Mtok$0.75$0.39
Output $/Mtok$3.75$2.34
Coding index58.0Not benchmarked
Independent measurements behind it61
Cost per solved task$1.78Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 3.7 Flash better than Qwen3.5 397B A17B for coding?

Only Gemini 3.7 Flash has a coding score, 58.0 on the Vibe Coding Index; Qwen3.5 397B A17B has none, so the two cannot be ranked on coding. Pick Qwen3.5 397B A17B for output tokens 1.6x cheaper ($2.34 vs $3.75 per million).

Which is cheaper, Gemini 3.7 Flash or Qwen3.5 397B A17B?

Gemini 3.7 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; Qwen3.5 397B A17B costs $0.39 and $2.34. Cost per solved task is known for Gemini 3.7 Flash only.

Which has the bigger context window, Gemini 3.7 Flash or Qwen3.5 397B A17B?

Gemini 3.7 Flash, with 1.05M tokens against 262K.

How many benchmarks is the Gemini 3.7 Flash vs Qwen3.5 397B A17B comparison based on?

60 benchmarks have a result for both models as of October 22, 2026. Gemini 3.7 Flash's coding index rests on 6 independent benchmarks and Qwen3.5 397B A17B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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