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Gemini 2.5 Flash vs Qwen3.5 397B A17B

Updated October 21, 2026. 55 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace Gemini 2.5 Flash Replace Qwen3.5 397B A17B
Gemini 2.5 FlashGoogle
Coding
28.7
Overall
15.5
Output $/M
$2.50
2
Qwen3.5 397B A17BQwen
Coding
28.6
Overall
21.4
Output $/M
$2.34
53
vs boards won of 55 shared

Decision reading

Gemini 2.5 Flash and Qwen3.5 397B A17B are level for coding, 28.7 against 28.6 on the Vibe Coding Index, so price and context decide.

Pick Qwen3.5 397B A17B when output tokens cost 1.1x less, or when what matters is Terminal-Bench Hard (Artificial Analysis run) or LMArena Text: coding, where it leads. Pick Gemini 2.5 Flash when the context window is larger, 1.05M against 262K tokens, or when what matters is LMArena Text: Korean or LMArena Vision: captioning, where it leads.

Model AGemini 2.5 FlashGoogle28.7/1001 independent benchmark$0.466 per solved taskModel BQwen3.5 397B A17BQwen28.6/1001 independent benchmarkNo cost per solved task
Shared results
55
Gemini 2.5 Flash only
14
Qwen3.5 397B A17B only
10
Like-for-like categories
8 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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 2.5 Flash 28.7 from 1 benchmark, Qwen3.5 397B A17B 28.6 from 1 benchmark.
Widest category
Agentic work, 64.0 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: Gemini 2.5 Flash 31.6% against Qwen3.5 397B A17B 95.6%, 64.0 points apart on a 0 to 100 scale.
Output price
Gemini 2.5 Flash $2.50 against Qwen3.5 397B A17B $2.34 per million output tokens, 1.1x apart.
Context window
Gemini 2.5 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 2.5 FlashBarsQwen3.5 397B A17BTies
Coding03
Intelligence02
Agentic work01
Reasoning07
Math02
Knowledge04
Web design07
General227
All shared boards253
CodingLike-for-likeFour of these boards feed the Vibe Coding Index03
Coding benchmarks for Gemini 2.5 Flash and Qwen3.5 397B A17B
BenchmarkGemini 2.5 FlashQwen3.5 397B A17BLeader
SWE-bench Verified28.7%Not measuredOnly Gemini 2.5 Flash measured
LMArena WebDevNot measured1400Only Qwen3.5 397B A17B measured
LiveCodeBench (Artificial Analysis run)69.5%Not measuredOnly Gemini 2.5 Flash measured
SciCodeNot measured44.8%Only Qwen3.5 397B A17B measured
Terminal-Bench Hard (Artificial Analysis run)13.6%40.9%Qwen3.5 397B A17B
Terminal-Bench17.1%Not measuredOnly Gemini 2.5 Flash measured
ALE-BenchNot measured621.9Only Qwen3.5 397B A17B measured
LMArena Text: coding14231464Qwen3.5 397B A17B
LMArena Text: software and IT14251463Qwen3.5 397B A17B
LMArena WebDev: ReactNot measured1388Only Qwen3.5 397B A17B measured
LMArena WebDev: HTMLNot measured1410Only Qwen3.5 397B A17B measured
Neither model has a result on the other 27 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Gemini 2.5 Flash and Qwen3.5 397B A17B
BenchmarkGemini 2.5 FlashQwen3.5 397B A17BLeader
AA Intelligence Index15.521.4Qwen3.5 397B A17B
Epoch Capabilities Index142.9146.8Qwen3.5 397B A17B
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Gemini 2.5 Flash and Qwen3.5 397B A17B
BenchmarkGemini 2.5 FlashQwen3.5 397B A17BLeader
τ²-Bench Telecom31.6%95.6%Qwen3.5 397B A17B
APEX-AgentsNot measured24.9%Only Qwen3.5 397B A17B measured
BALROG33.5%Not measuredOnly Gemini 2.5 Flash measured
Vending-Bench 2$549Not measuredOnly Gemini 2.5 Flash measured
Neither model has a result on the other 35 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index07
Reasoning benchmarks for Gemini 2.5 Flash and Qwen3.5 397B A17B
BenchmarkGemini 2.5 FlashQwen3.5 397B A17BLeader
GPQA Diamond (Artificial Analysis run)79.0%89.3%Qwen3.5 397B A17B
Humanity's Last Exam (Artificial Analysis run)12.1%29.0%Qwen3.5 397B A17B
GPQA Diamond (Epoch AI run)Not measured86.4%Only Qwen3.5 397B A17B measured
ARC-AGI33.3%Not measuredOnly Gemini 2.5 Flash measured
ARC-AGI-22.5%Not measuredOnly Gemini 2.5 Flash measured
SimpleBench41.2%Not measuredOnly Gemini 2.5 Flash measured
Mystery game puzzlesNot measured18.0%Only Qwen3.5 397B A17B measured
LMArena Text: hard prompts14221448Qwen3.5 397B A17B
LMArena Text: expert14261462Qwen3.5 397B A17B
LMArena Text: hard prompts in English14201450Qwen3.5 397B A17B
LMArena Vision: diagrams12451277Qwen3.5 397B A17B
LMArena Vision: homework12441292Qwen3.5 397B A17B
Neither model has a result on the other 9 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Gemini 2.5 Flash and Qwen3.5 397B A17B
BenchmarkGemini 2.5 FlashQwen3.5 397B A17BLeader
AA Math Index73.3Not measuredOnly Gemini 2.5 Flash measured
AIME 2025 (Artificial Analysis run)73.3%Not measuredOnly Gemini 2.5 Flash measured
OTIS Mock AIMENot measured88.9%Only Qwen3.5 397B A17B measured
FrontierMath, tiers 1 to 3Not measured31.2%Only Qwen3.5 397B A17B measured
LMArena Text: math14111453Qwen3.5 397B A17B
LMArena Text: mathematical work14221454Qwen3.5 397B A17B
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Gemini 2.5 Flash and Qwen3.5 397B A17B
BenchmarkGemini 2.5 FlashQwen3.5 397B A17BLeader
MedCode (Vals AI)40.4%Not measuredOnly Gemini 2.5 Flash measured
MMLU Pro (Artificial Analysis run)83.2%Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: science14331457Qwen3.5 397B A17B
LMArena Text: medicine and healthcare14281455Qwen3.5 397B A17B
LMArena Text: legal and government14301441Qwen3.5 397B A17B
LMArena Text: business and finance14041435Qwen3.5 397B A17B
Neither model has a result on the other 11 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index07
Web design benchmarks for Gemini 2.5 Flash and Qwen3.5 397B A17B
BenchmarkGemini 2.5 FlashQwen3.5 397B A17BLeader
Design Arena: websites10741191Qwen3.5 397B A17B
Design Arena: UI components10051163Qwen3.5 397B A17B
Design Arena: game dev10051141Qwen3.5 397B A17B
Design Arena: data viz10601175Qwen3.5 397B A17B
Design Arena: 3D10211161Qwen3.5 397B A17B
Design Arena: all code categories10591180Qwen3.5 397B A17B
Design Arena: SVG10181139Qwen3.5 397B A17B
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index227
General benchmarks for Gemini 2.5 Flash and Qwen3.5 397B A17B
BenchmarkGemini 2.5 FlashQwen3.5 397B A17BLeader
SAGE (Vals AI)44.8%Not measuredOnly Gemini 2.5 Flash measured
MedScribe (Vals AI)83.0%Not measuredOnly Gemini 2.5 Flash measured
IFBench50.3%78.8%Qwen3.5 397B A17B
Long context reasoning (AA-LCR)65.3%77.3%Qwen3.5 397B A17B
DTBench76.5%87.5%Qwen3.5 397B A17B
LMCA27.5%37.9%Qwen3.5 397B A17B
LMArena Text14171437Qwen3.5 397B A17B
LMArena Text: instruction following14051424Qwen3.5 397B A17B
LMArena Text: creative writing14001402Qwen3.5 397B A17B
LMArena Vision12351262Qwen3.5 397B A17B
LMArena Text: English14181443Qwen3.5 397B A17B
LMArena Text: non-English14091430Qwen3.5 397B A17B
LMArena Text: Chinese14491498Qwen3.5 397B A17B
LMArena Text: German14171445Qwen3.5 397B A17B
LMArena Text: Japanese13961429Qwen3.5 397B A17B
LMArena Text: Korean13851384Gemini 2.5 Flash
LMArena Text: French14321462Qwen3.5 397B A17B
LMArena Text: Spanish14221441Qwen3.5 397B A17B
LMArena Text: Russian14151430Qwen3.5 397B A17B
LMArena Text: Polish14131447Qwen3.5 397B A17B
LMArena Text: multi-turn14081446Qwen3.5 397B A17B
LMArena Text: longer queries14191441Qwen3.5 397B A17B
LMArena Text: writing and language14051415Qwen3.5 397B A17B
LMArena Text: entertainment and media13931399Qwen3.5 397B A17B
LMArena Vision: English12391268Qwen3.5 397B A17B
LMArena Vision: Chinese12841314Qwen3.5 397B A17B
LMArena Vision: reading text12371271Qwen3.5 397B A17B
LMArena Vision: humor12251262Qwen3.5 397B A17B
LMArena Vision: captioning12771230Gemini 2.5 Flash
LMArena Vision: recognizing things12521265Qwen3.5 397B A17B
LMArena Vision: creative writing12411260Qwen3.5 397B A17B
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 2.5 Flash and Qwen3.5 397B A17B
BenchmarkGemini 2.5 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 2.5 Flash$0.0015Fits in one request
Qwen3.5 397B A17B$0.0016Fits in one request

Gemini 2.5 Flash costs less

Repository review

50K input + 3K output tokens

Gemini 2.5 Flash$0.022Fits in one request
Qwen3.5 397B A17B$0.027Fits in one request

Gemini 2.5 Flash costs less

Agent loop

200K input + 10K output tokens

Gemini 2.5 Flash$0.085Fits in one request
Qwen3.5 397B A17B$0.101Fits in one request

Gemini 2.5 Flash 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 2.5 Flash and Qwen3.5 397B A17B
SpecificationGoogle Gemini 2.5 FlashQwen3.5 397B A17B
MakerGoogleQwen
WeightsNo public weights listedOpen weights
ReleasedJune 17, 2025February 16, 2026
Context window1.05M262K
Input $/Mtok$0.30$0.39
Output $/Mtok$2.50$2.34
Coding index28.728.6
Independent measurements behind it11
Cost per solved task$0.466Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 2.5 Flash better than Qwen3.5 397B A17B for coding?

Gemini 2.5 Flash and Qwen3.5 397B A17B are level for coding, 28.7 against 28.6 on the Vibe Coding Index, so price and context decide. Pick Qwen3.5 397B A17B when output tokens cost 1.1x less, or when what matters is Terminal-Bench Hard (Artificial Analysis run) or LMArena Text: coding, where it leads. Pick Gemini 2.5 Flash when the context window is larger, 1.05M against 262K tokens, or when what matters is LMArena Text: Korean or LMArena Vision: captioning, where it leads.

Which is cheaper, Gemini 2.5 Flash or Qwen3.5 397B A17B?

Gemini 2.5 Flash costs $0.30 per million input tokens and $2.50 per million output tokens; Qwen3.5 397B A17B costs $0.39 and $2.34. Cost per solved task is known for Gemini 2.5 Flash only.

Which has the bigger context window, Gemini 2.5 Flash or Qwen3.5 397B A17B?

Gemini 2.5 Flash, with 1.05M tokens against 262K.

How many benchmarks is the Gemini 2.5 Flash vs Qwen3.5 397B A17B comparison based on?

55 benchmarks have a result for both models as of October 21, 2026. Gemini 2.5 Flash's coding index rests on 1 independent benchmark 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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