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Gemini 2.5 Pro vs Qwen3.5 397B A17B

Qwen3.5 397B A17B leads Gemini 2.5 Pro on the Artificial Analysis Intelligence Index, 21.4 to 16.1, and Qwen3.5 397B A17B costs 4.3x less per output token ($2.34 vs $10.00 per million). Updated October 22, 2026; 61 benchmarks have a result for both.

Replace Gemini 2.5 Pro Replace Qwen3.5 397B A17B
Gemini 2.5 ProGoogle
Coding
19.1
Overall
41.8
Output $/M
$10.00
31
Qwen3.5 397B A17BQwen
Coding
No data
Overall
57.1
Output $/M
$2.34
30
vs boards won of 61 shared

Gemini 2.5 Pro or Qwen3.5 397B A17B: which to pick

Only Gemini 2.5 Pro has a coding score, 19.1 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 4.3x cheaper ($2.34 vs $10.00 per million) and work measured by LMArena WebDev or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Model AGemini 2.5 ProGoogle19.1/1003 independent benchmarks$0.64 per solved taskModel BQwen3.5 397B A17BQwenNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
61
Gemini 2.5 Pro only
33
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 2.5 Pro 19.1 from 3 benchmarks, Qwen3.5 397B A17B not benchmarked.
Widest category
Agentic work, 41.5 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: Gemini 2.5 Pro 54.1% against Qwen3.5 397B A17B 95.6%, 41.5 points apart on a 0 to 100 scale.
Output price
Gemini 2.5 Pro $10.00 against Qwen3.5 397B A17B $2.34 per million output tokens, 4.3x apart.
Context window
Gemini 2.5 Pro 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 ProBarsQwen3.5 397B A17BTies
Coding15
Intelligence02
Agentic work01
Reasoning26
Math14
Knowledge40
Web design15
General227
All shared boards3130
CodingLike-for-likeSix of these boards feed the Vibe Coding Index15
Coding benchmarks for Gemini 2.5 Pro and Qwen3.5 397B A17B
BenchmarkGemini 2.5 ProQwen3.5 397B A17BLeader
SWE-bench Verified53.6%Not measuredOnly Gemini 2.5 Pro measured
LMArena WebDev12261400Qwen3.5 397B A17B
AA Coding Index33.3Not measuredOnly Gemini 2.5 Pro measured
SWE-bench Verified (Vals AI)54.4%Not measuredOnly Gemini 2.5 Pro measured
Vibe Code Bench (Vals AI)0.4%Not measuredOnly Gemini 2.5 Pro measured
LiveCodeBench (Artificial Analysis run)80.1%Not measuredOnly Gemini 2.5 Pro measured
SciCode46.3%44.8%Gemini 2.5 Pro
Terminal-Bench Hard (Artificial Analysis run)26.5%40.9%Qwen3.5 397B A17B
Terminal-Bench32.6%Not measuredOnly Gemini 2.5 Pro measured
GSO-Bench3.9%Not measuredOnly Gemini 2.5 Pro measured
WeirdML54.0%Not measuredOnly Gemini 2.5 Pro measured
ALE-BenchNot measured621.9Only Qwen3.5 397B A17B measured
LMArena Text: coding14521464Qwen3.5 397B A17B
LMArena Text: software and IT14591463Qwen3.5 397B A17B
LMArena WebDev: ReactNot measured1388Only Qwen3.5 397B A17B measured
LMArena WebDev: HTML12351410Qwen3.5 397B A17B
LMArena WebDev: from an image1285Not measuredOnly Gemini 2.5 Pro measured
Neither model has a result on the other 26 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Gemini 2.5 Pro and Qwen3.5 397B A17B
BenchmarkGemini 2.5 ProQwen3.5 397B A17BLeader
AA Intelligence Index16.121.4Qwen3.5 397B A17B
Epoch Capabilities Index145.1146.8Qwen3.5 397B A17B
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Gemini 2.5 Pro and Qwen3.5 397B A17B
BenchmarkGemini 2.5 ProQwen3.5 397B A17BLeader
AA Agentic Index1.6Not measuredOnly Gemini 2.5 Pro measured
τ²-Bench Telecom54.1%95.6%Qwen3.5 397B A17B
APEX-AgentsNot measured24.9%Only Qwen3.5 397B A17B measured
GDPval23.3%Not measuredOnly Gemini 2.5 Pro measured
DeepResearch Bench41.5%Not measuredOnly Gemini 2.5 Pro measured
Vending-Bench 2$574Not measuredOnly Gemini 2.5 Pro measured
BrowseComp-Plus29.5%Not measuredOnly Gemini 2.5 Pro measured
Neither model has a result on the other 35 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index26
Reasoning benchmarks for Gemini 2.5 Pro and Qwen3.5 397B A17B
BenchmarkGemini 2.5 ProQwen3.5 397B A17BLeader
GPQA Diamond (Artificial Analysis run)84.4%89.3%Qwen3.5 397B A17B
Humanity's Last Exam (Artificial Analysis run)22.5%29.0%Qwen3.5 397B A17B
GPQA Diamond (Epoch AI run)85.3%86.4%Qwen3.5 397B A17B
ARC-AGI41.0%Not measuredOnly Gemini 2.5 Pro measured
ARC-AGI-24.9%Not measuredOnly Gemini 2.5 Pro measured
Mystery game puzzlesNot measured18.0%Only Qwen3.5 397B A17B measured
LMArena Text: hard prompts14551448Gemini 2.5 Pro
LMArena Text: expert14521462Qwen3.5 397B A17B
LMArena Text: hard prompts in English14531450Gemini 2.5 Pro
LMArena Vision: diagrams12741277Qwen3.5 397B A17B
LMArena Vision: homework12811292Qwen3.5 397B A17B
Kagi LLM Benchmark70.3%Not measuredOnly Gemini 2.5 Pro measured
Neither model has a result on the other 11 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index14
Math benchmarks for Gemini 2.5 Pro and Qwen3.5 397B A17B
BenchmarkGemini 2.5 ProQwen3.5 397B A17BLeader
AA Math Index87.7Not measuredOnly Gemini 2.5 Pro measured
AIME 2025 (Artificial Analysis run)87.7%Not measuredOnly Gemini 2.5 Pro measured
OTIS Mock AIME84.7%88.9%Qwen3.5 397B A17B
FrontierMath, tiers 1 to 324.6%31.2%Qwen3.5 397B A17B
FrontierMath, tier 40.0%Not measuredOnly Gemini 2.5 Pro measured
LMArena Text: math14501453Qwen3.5 397B A17B
LMArena Text: mathematical work14541454Gemini 2.5 Pro
MathArena12.7%19.2%Qwen3.5 397B A17B
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for Gemini 2.5 Pro and Qwen3.5 397B A17B
BenchmarkGemini 2.5 ProQwen3.5 397B A17BLeader
CaseLaw (Vals AI)63.9%Not measuredOnly Gemini 2.5 Pro measured
CorpFin (Vals AI)60.8%Not measuredOnly Gemini 2.5 Pro measured
MortgageTax (Vals AI)68.9%Not measuredOnly Gemini 2.5 Pro measured
MedCode (Vals AI)50.6%Not measuredOnly Gemini 2.5 Pro measured
MMLU Pro (Artificial Analysis run)86.2%Not measuredOnly Gemini 2.5 Pro measured
LMArena Text: science14801457Gemini 2.5 Pro
LMArena Text: medicine and healthcare14761455Gemini 2.5 Pro
LMArena Text: legal and government14801441Gemini 2.5 Pro
LMArena Text: business and finance14391435Gemini 2.5 Pro
FACTS Benchmark Suite61.5%Not measuredOnly Gemini 2.5 Pro measured
PRBench Finance38.9%Not measuredOnly Gemini 2.5 Pro measured
PRBench Legal41.4%Not measuredOnly Gemini 2.5 Pro measured
Neither model has a result on the other 8 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index15
Web design benchmarks for Gemini 2.5 Pro and Qwen3.5 397B A17B
BenchmarkGemini 2.5 ProQwen3.5 397B A17BLeader
Design Arena: websites11671190Qwen3.5 397B A17B
Design Arena: UI components11371161Qwen3.5 397B A17B
Design Arena: game dev11111140Qwen3.5 397B A17B
Design Arena: data viz12221175Gemini 2.5 Pro
Design Arena: 3D10801160Qwen3.5 397B A17B
Design Arena: all code categories11521179Qwen3.5 397B A17B
Design Arena: SVGNot measured1139Only Qwen3.5 397B A17B measured
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 Pro and Qwen3.5 397B A17B
BenchmarkGemini 2.5 ProQwen3.5 397B A17BLeader
SAGE (Vals AI)41.9%Not measuredOnly Gemini 2.5 Pro measured
MedScribe (Vals AI)73.5%Not measuredOnly Gemini 2.5 Pro measured
IFBench48.7%78.8%Qwen3.5 397B A17B
Long context reasoning (AA-LCR)69.0%77.3%Qwen3.5 397B A17B
DTBench82.4%87.5%Qwen3.5 397B A17B
LMCA34.8%37.9%Qwen3.5 397B A17B
Creative writing (Lech Mazur)83.8%Not measuredOnly Gemini 2.5 Pro measured
LMArena Text14581437Gemini 2.5 Pro
LMArena Text: instruction following14371424Gemini 2.5 Pro
LMArena Text: creative writing14541402Gemini 2.5 Pro
LMArena Vision12631262Gemini 2.5 Pro
LMArena Text: English14581443Gemini 2.5 Pro
LMArena Text: non-English14521430Gemini 2.5 Pro
LMArena Text: Chinese15071498Gemini 2.5 Pro
LMArena Text: German14871445Gemini 2.5 Pro
LMArena Text: Japanese14611429Gemini 2.5 Pro
LMArena Text: Korean14341384Gemini 2.5 Pro
LMArena Text: French14731462Gemini 2.5 Pro
LMArena Text: Spanish14741441Gemini 2.5 Pro
LMArena Text: Russian14611430Gemini 2.5 Pro
LMArena Text: Polish14791447Gemini 2.5 Pro
LMArena Text: multi-turn14531446Gemini 2.5 Pro
LMArena Text: longer queries14491441Gemini 2.5 Pro
LMArena Text: writing and language14541415Gemini 2.5 Pro
LMArena Text: entertainment and media14411399Gemini 2.5 Pro
LMArena Vision: English12611268Qwen3.5 397B A17B
LMArena Vision: Chinese13001314Qwen3.5 397B A17B
LMArena Vision: reading text12701271Qwen3.5 397B A17B
LMArena Vision: humor12621262Gemini 2.5 Pro
LMArena Vision: captioning13041230Gemini 2.5 Pro
LMArena Vision: recognizing things12831265Gemini 2.5 Pro
LMArena Vision: creative writing12651260Gemini 2.5 Pro
LMArena Document1421Not measuredOnly Gemini 2.5 Pro measured
MultiChallenge53.6%Not measuredOnly Gemini 2.5 Pro measured
Neither model has a result on the other 14 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemini 2.5 Pro and Qwen3.5 397B A17B
BenchmarkGemini 2.5 ProQwen3.5 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 Pro$0.0063Fits 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 2.5 Pro$0.092Fits 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 2.5 Pro$0.350Fits 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 2.5 Pro and Qwen3.5 397B A17B
SpecificationGoogle Gemini 2.5 ProQwen3.5 397B A17B
MakerGoogleQwen
WeightsNo public weights listedOpen weights
ReleasedJune 17, 2025February 16, 2026
Context window1.05M262K
Input $/Mtok$1.25$0.39
Output $/Mtok$10.00$2.34
Coding index19.1Not benchmarked
Independent measurements behind it31
Cost per solved task$0.64Not computable
SourceOpenRouter listingOpenRouter listing

Questions

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

Only Gemini 2.5 Pro has a coding score, 19.1 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 4.3x cheaper ($2.34 vs $10.00 per million) and work measured by LMArena WebDev or Terminal-Bench Hard (Artificial Analysis run), where it leads.

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

Gemini 2.5 Pro costs $1.25 per million input tokens and $10.00 per million output tokens; Qwen3.5 397B A17B costs $0.39 and $2.34. Cost per solved task is known for Gemini 2.5 Pro only.

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

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

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

61 benchmarks have a result for both models as of October 22, 2026. Gemini 2.5 Pro's coding index rests on 3 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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