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Gemini 3.7 Flash vs Qwen3.5-122B-A10B

Gemini 3.7 Flash leads Qwen3.5-122B-A10B on the Artificial Analysis Intelligence Index, 39.6 to 17.7, and Qwen3.5-122B-A10B costs 1.8x less per output token ($2.08 vs $3.75 per million). Updated October 22, 2026; 48 benchmarks have a result for both.

Replace Gemini 3.7 Flash Replace Qwen3.5-122B-A10B
Gemini 3.7 FlashGoogle
Coding
58.0
Overall
65.7
Output $/M
$3.75
48
Qwen3.5-122B-A10BQwen
Coding
No data
Overall
No data
Output $/M
$2.08
0
vs boards won of 48 shared

Gemini 3.7 Flash or Qwen3.5-122B-A10B: which to pick

Only Gemini 3.7 Flash has a coding score, 58.0 on the Vibe Coding Index; Qwen3.5-122B-A10B has none, so the two cannot be ranked on coding.

Pick Qwen3.5-122B-A10B for output tokens 1.8x cheaper ($2.08 vs $3.75 per million).

Model AGemini 3.7 FlashGoogle58.0/1006 independent benchmarks$1.78 per solved taskModel BQwen3.5-122B-A10BQwenNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
48
Gemini 3.7 Flash only
66
Qwen3.5-122B-A10B only
3
Like-for-like categories
6 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, Qwen3.5-122B-A10B not benchmarked.
Widest category
Coding, 25.9 points apart on average over 7 shared benchmarks.
Widest single gap
LMArena WebDev: HTML: Gemini 3.7 Flash 1593 against Qwen3.5-122B-A10B 1351, 40.3 points apart on a 0 to 100 scale.
Output price
Gemini 3.7 Flash $3.75 against Qwen3.5-122B-A10B $2.08 per million output tokens, 1.8x apart.
Context window
Gemini 3.7 Flash takes 1.05M tokens, Qwen3.5-122B-A10B 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 FlashBarsQwen3.5-122B-A10BTies
Coding70
Intelligence10
Reasoning80
Math20
Knowledge40
General260
All shared boards480
CodingLike-for-likeSix of these boards feed the Vibe Coding Index70
Coding benchmarks for Gemini 3.7 Flash and Qwen3.5-122B-A10B
BenchmarkGemini 3.7 FlashQwen3.5-122B-A10BLeader
LiveBench coding80.5%Not measuredOnly Gemini 3.7 Flash measured
LMArena WebDev15911361Gemini 3.7 Flash
AA Coding Index71.543.3Gemini 3.7 Flash
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%39.7%Gemini 3.7 Flash
Terminal-Bench Hard (Artificial Analysis run)Not measured31.1%Only Qwen3.5-122B-A10B measured
FrontierCode43.6%Not measuredOnly Gemini 3.7 Flash measured
FrontierSWE20.3%Not measuredOnly Gemini 3.7 Flash measured
ALE-Bench904.3Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: coding14991436Gemini 3.7 Flash
LMArena Text: software and IT14981436Gemini 3.7 Flash
LMArena WebDev: React15871353Gemini 3.7 Flash
LMArena WebDev: HTML15931351Gemini 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 index10
Intelligence benchmarks for Gemini 3.7 Flash and Qwen3.5-122B-A10B
BenchmarkGemini 3.7 FlashQwen3.5-122B-A10BLeader
AA Intelligence Index39.617.7Gemini 3.7 Flash
Epoch Capabilities Index158.0Not measuredOnly Gemini 3.7 Flash measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index19 boards, none shared
Agentic work benchmarks for Gemini 3.7 Flash and Qwen3.5-122B-A10B
BenchmarkGemini 3.7 FlashQwen3.5-122B-A10BLeader
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 measured93.6%Only Qwen3.5-122B-A10B measured
APEX-Agents67.8%Not measuredOnly Gemini 3.7 Flash measured
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 index80
Reasoning benchmarks for Gemini 3.7 Flash and Qwen3.5-122B-A10B
BenchmarkGemini 3.7 FlashQwen3.5-122B-A10BLeader
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%85.7%Gemini 3.7 Flash
Humanity's Last Exam (Artificial Analysis run)47.9%25.2%Gemini 3.7 Flash
GPQA Diamond (Epoch AI run)94.8%Not measuredOnly Gemini 3.7 Flash measured
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%17.0%Gemini 3.7 Flash
LMArena Text: hard prompts14951421Gemini 3.7 Flash
LMArena Text: expert15121431Gemini 3.7 Flash
LMArena Text: hard prompts in English14871431Gemini 3.7 Flash
LMArena Vision: diagrams13291249Gemini 3.7 Flash
LMArena Vision: homework13201261Gemini 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 index20
Math benchmarks for Gemini 3.7 Flash and Qwen3.5-122B-A10B
BenchmarkGemini 3.7 FlashQwen3.5-122B-A10BLeader
OTIS Mock AIME97.2%Not measuredOnly Gemini 3.7 Flash measured
FrontierMath, tiers 1 to 371.6%Not measuredOnly Gemini 3.7 Flash measured
FrontierMath, tier 436.6%Not measuredOnly Gemini 3.7 Flash measured
ProofBench58.0%Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: math15111431Gemini 3.7 Flash
LMArena Text: mathematical work15021431Gemini 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 Qwen3.5-122B-A10B
BenchmarkGemini 3.7 FlashQwen3.5-122B-A10BLeader
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: science15111432Gemini 3.7 Flash
LMArena Text: medicine and healthcare14941423Gemini 3.7 Flash
LMArena Text: legal and government14961422Gemini 3.7 Flash
LMArena Text: business and finance14791414Gemini 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 designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Web design benchmarks for Gemini 3.7 Flash and Qwen3.5-122B-A10B
BenchmarkGemini 3.7 FlashQwen3.5-122B-A10BLeader
Design Arena: websites1303Not measuredOnly Gemini 3.7 Flash measured
Design Arena: UI components1296Not measuredOnly Gemini 3.7 Flash measured
Design Arena: game dev1317Not measuredOnly Gemini 3.7 Flash measured
Design Arena: data viz1315Not measuredOnly Gemini 3.7 Flash measured
Design Arena: 3D1307Not measuredOnly Gemini 3.7 Flash measured
Design Arena: all code categories1308Not measuredOnly Gemini 3.7 Flash measured
Design Arena: SVG1283Not measuredOnly Gemini 3.7 Flash measured
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 Qwen3.5-122B-A10B
BenchmarkGemini 3.7 FlashQwen3.5-122B-A10BLeader
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 measured75.7%Only Qwen3.5-122B-A10B measured
Long context reasoning (AA-LCR)83.0%76.3%Gemini 3.7 Flash
DTBench96.8%84.3%Gemini 3.7 Flash
LMCA50.4%32.2%Gemini 3.7 Flash
Furniture assembly26.7%Not measuredOnly Gemini 3.7 Flash measured
LMArena Text14891417Gemini 3.7 Flash
LMArena Text: instruction following14841399Gemini 3.7 Flash
LMArena Text: creative writing14881368Gemini 3.7 Flash
LMArena Vision13141244Gemini 3.7 Flash
LMArena Text: English14831428Gemini 3.7 Flash
LMArena Text: non-English14871401Gemini 3.7 Flash
LMArena Text: Chinese15521463Gemini 3.7 Flash
LMArena Text: German15061425Gemini 3.7 Flash
LMArena Text: Japanese15111367Gemini 3.7 Flash
LMArena Text: Korean14811353Gemini 3.7 Flash
LMArena Text: French15001443Gemini 3.7 Flash
LMArena Text: Spanish14951425Gemini 3.7 Flash
LMArena Text: Russian15151400Gemini 3.7 Flash
LMArena Text: Polish15031398Gemini 3.7 Flash
LMArena Text: multi-turn14851416Gemini 3.7 Flash
LMArena Text: longer queries14921410Gemini 3.7 Flash
LMArena Text: writing and language14911387Gemini 3.7 Flash
LMArena Text: entertainment and media14771366Gemini 3.7 Flash
LMArena Vision: English13091249Gemini 3.7 Flash
LMArena Vision: Chinese13941301Gemini 3.7 Flash
LMArena Vision: reading text13221251Gemini 3.7 Flash
LMArena Vision: humor12991243Gemini 3.7 Flash
LMArena Vision: creative writing13121220Gemini 3.7 Flash
Neither model has a result on the other 15 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 Qwen3.5-122B-A10B
BenchmarkGemini 3.7 FlashQwen3.5-122B-A10BLeader
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
Qwen3.5-122B-A10B$0.0013Fits in one request

Qwen3.5-122B-A10B costs less

Repository review

50K input + 3K output tokens

Gemini 3.7 Flash$0.049Fits in one request
Qwen3.5-122B-A10B$0.019Fits in one request

Qwen3.5-122B-A10B costs less

Agent loop

200K input + 10K output tokens

Gemini 3.7 Flash$0.188Fits in one request
Qwen3.5-122B-A10B$0.073Fits in one request

Qwen3.5-122B-A10B 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 Qwen3.5-122B-A10B
SpecificationGoogle Gemini 3.7 FlashQwen3.5-122B-A10B
MakerGoogleQwen
WeightsNo public weights listedOpen weights
ReleasedAugust 13, 2026February 25, 2026
Context window1.05M262K
Input $/Mtok$0.75$0.26
Output $/Mtok$3.75$2.08
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 Qwen3.5-122B-A10B for coding?

Only Gemini 3.7 Flash has a coding score, 58.0 on the Vibe Coding Index; Qwen3.5-122B-A10B has none, so the two cannot be ranked on coding. Pick Qwen3.5-122B-A10B for output tokens 1.8x cheaper ($2.08 vs $3.75 per million).

Which is cheaper, Gemini 3.7 Flash or Qwen3.5-122B-A10B?

Gemini 3.7 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; Qwen3.5-122B-A10B costs $0.26 and $2.08. Cost per solved task is known for Gemini 3.7 Flash only.

Which has the bigger context window, Gemini 3.7 Flash or Qwen3.5-122B-A10B?

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

How many benchmarks is the Gemini 3.7 Flash vs Qwen3.5-122B-A10B comparison based on?

48 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 Qwen3.5-122B-A10B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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