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Gemini 2.5 Pro vs Qwen3.5-122B-A10B

Updated October 21, 2026. 49 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 Pro Replace Qwen3.5-122B-A10B
Gemini 2.5 ProGoogle
Coding
37.0
Overall
16.1
Output $/M
$10.00
37
Qwen3.5-122B-A10BQwen
Coding
22.9
Overall
17.7
Output $/M
$2.08
12
vs boards won of 49 shared

Decision reading

Pick Gemini 2.5 Pro for coding: it scores 37.0 on the Vibe Coding Index against 22.9 for Qwen3.5-122B-A10B.

Pick Qwen3.5-122B-A10B when output tokens cost 4.8x less, or when what matters is LMArena WebDev or AA Coding Index, where it leads.

Model AGemini 2.5 ProGoogle37.0/1002 independent benchmarks$0.64 per solved taskModel BQwen3.5-122B-A10BQwen22.9/1001 independent benchmarkNo cost per solved task
Shared results
49
Gemini 2.5 Pro only
38
Qwen3.5-122B-A10B only
2
Like-for-like categories
7 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 Pro 37.0 from 2 benchmarks, Qwen3.5-122B-A10B 22.9 from 1 benchmark.
Widest category
Agentic work, 39.5 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: Gemini 2.5 Pro 54.1% against Qwen3.5-122B-A10B 93.6%, 39.5 points apart on a 0 to 100 scale.
Output price
Gemini 2.5 Pro $10.00 against Qwen3.5-122B-A10B $2.08 per million output tokens, 4.8x apart.
Context window
Gemini 2.5 Pro 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 2.5 ProBarsQwen3.5-122B-A10BTies
Coding34
Intelligence01
Agentic work01
Reasoning52
Math20
Knowledge40
General234
All shared boards3712
CodingLike-for-likeFour of these boards feed the Vibe Coding Index34
Coding benchmarks for Gemini 2.5 Pro and Qwen3.5-122B-A10B
BenchmarkGemini 2.5 ProQwen3.5-122B-A10BLeader
SWE-bench Verified53.6%Not measuredOnly Gemini 2.5 Pro measured
LMArena WebDev12261361Qwen3.5-122B-A10B
AA Coding Index33.343.3Qwen3.5-122B-A10B
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%39.7%Gemini 2.5 Pro
Terminal-Bench Hard (Artificial Analysis run)26.5%31.1%Qwen3.5-122B-A10B
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
LMArena Text: coding14521436Gemini 2.5 Pro
LMArena Text: software and IT14591436Gemini 2.5 Pro
LMArena WebDev: ReactNot measured1353Only Qwen3.5-122B-A10B measured
LMArena WebDev: HTML12351351Qwen3.5-122B-A10B
LMArena WebDev: from an image1285Not measuredOnly Gemini 2.5 Pro measured
Neither model has a result on the other 22 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Gemini 2.5 Pro and Qwen3.5-122B-A10B
BenchmarkGemini 2.5 ProQwen3.5-122B-A10BLeader
AA Intelligence Index16.117.7Qwen3.5-122B-A10B
Epoch Capabilities Index145.1Not measuredOnly Gemini 2.5 Pro measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Gemini 2.5 Pro and Qwen3.5-122B-A10B
BenchmarkGemini 2.5 ProQwen3.5-122B-A10BLeader
AA Agentic Index1.6Not measuredOnly Gemini 2.5 Pro measured
τ²-Bench Telecom54.1%93.6%Qwen3.5-122B-A10B
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
Neither model has a result on the other 34 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index52
Reasoning benchmarks for Gemini 2.5 Pro and Qwen3.5-122B-A10B
BenchmarkGemini 2.5 ProQwen3.5-122B-A10BLeader
GPQA Diamond (Artificial Analysis run)84.4%85.7%Qwen3.5-122B-A10B
Humanity's Last Exam (Artificial Analysis run)22.5%25.2%Qwen3.5-122B-A10B
GPQA Diamond (Epoch AI run)85.3%Not measuredOnly Gemini 2.5 Pro measured
ARC-AGI41.0%Not measuredOnly Gemini 2.5 Pro measured
ARC-AGI-24.9%Not measuredOnly Gemini 2.5 Pro measured
Mystery game puzzlesNot measured17.0%Only Qwen3.5-122B-A10B measured
LMArena Text: hard prompts14551421Gemini 2.5 Pro
LMArena Text: expert14521431Gemini 2.5 Pro
LMArena Text: hard prompts in English14531431Gemini 2.5 Pro
LMArena Vision: diagrams12741249Gemini 2.5 Pro
LMArena Vision: homework12811261Gemini 2.5 Pro
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for Gemini 2.5 Pro and Qwen3.5-122B-A10B
BenchmarkGemini 2.5 ProQwen3.5-122B-A10BLeader
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%Not measuredOnly Gemini 2.5 Pro measured
FrontierMath, tiers 1 to 324.6%Not measuredOnly Gemini 2.5 Pro measured
FrontierMath, tier 40.0%Not measuredOnly Gemini 2.5 Pro measured
LMArena Text: math14501431Gemini 2.5 Pro
LMArena Text: mathematical work14541431Gemini 2.5 Pro
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 Qwen3.5-122B-A10B
BenchmarkGemini 2.5 ProQwen3.5-122B-A10BLeader
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: science14801432Gemini 2.5 Pro
LMArena Text: medicine and healthcare14761423Gemini 2.5 Pro
LMArena Text: legal and government14801422Gemini 2.5 Pro
LMArena Text: business and finance14391414Gemini 2.5 Pro
Neither model has a result on the other 8 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Web design benchmarks for Gemini 2.5 Pro and Qwen3.5-122B-A10B
BenchmarkGemini 2.5 ProQwen3.5-122B-A10BLeader
Design Arena: websites1167Not measuredOnly Gemini 2.5 Pro measured
Design Arena: UI components1139Not measuredOnly Gemini 2.5 Pro measured
Design Arena: game dev1112Not measuredOnly Gemini 2.5 Pro measured
Design Arena: data viz1222Not measuredOnly Gemini 2.5 Pro measured
Design Arena: 3D1080Not measuredOnly Gemini 2.5 Pro measured
Design Arena: all code categories1152Not measuredOnly Gemini 2.5 Pro measured
Neither model has a result on the other 3 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index234
General benchmarks for Gemini 2.5 Pro and Qwen3.5-122B-A10B
BenchmarkGemini 2.5 ProQwen3.5-122B-A10BLeader
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%75.7%Qwen3.5-122B-A10B
Long context reasoning (AA-LCR)69.0%76.3%Qwen3.5-122B-A10B
DTBench82.4%84.3%Qwen3.5-122B-A10B
LMCA34.8%32.2%Gemini 2.5 Pro
Creative writing (Lech Mazur)83.8%Not measuredOnly Gemini 2.5 Pro measured
LMArena Text14581417Gemini 2.5 Pro
LMArena Text: instruction following14371399Gemini 2.5 Pro
LMArena Text: creative writing14541368Gemini 2.5 Pro
LMArena Vision12631244Gemini 2.5 Pro
LMArena Text: English14581428Gemini 2.5 Pro
LMArena Text: non-English14521401Gemini 2.5 Pro
LMArena Text: Chinese15071463Gemini 2.5 Pro
LMArena Text: German14871425Gemini 2.5 Pro
LMArena Text: Japanese14611367Gemini 2.5 Pro
LMArena Text: Korean14341353Gemini 2.5 Pro
LMArena Text: French14731443Gemini 2.5 Pro
LMArena Text: Spanish14741425Gemini 2.5 Pro
LMArena Text: Russian14611400Gemini 2.5 Pro
LMArena Text: Polish14791398Gemini 2.5 Pro
LMArena Text: multi-turn14531416Gemini 2.5 Pro
LMArena Text: longer queries14491410Gemini 2.5 Pro
LMArena Text: writing and language14541387Gemini 2.5 Pro
LMArena Text: entertainment and media14411366Gemini 2.5 Pro
LMArena Vision: English12611249Gemini 2.5 Pro
LMArena Vision: Chinese13001301Qwen3.5-122B-A10B
LMArena Vision: reading text12701251Gemini 2.5 Pro
LMArena Vision: humor12621243Gemini 2.5 Pro
LMArena Vision: captioning1304Not measuredOnly Gemini 2.5 Pro measured
LMArena Vision: recognizing things1283Not measuredOnly Gemini 2.5 Pro measured
LMArena Vision: creative writing12651220Gemini 2.5 Pro
LMArena Document1421Not measuredOnly Gemini 2.5 Pro measured
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 2.5 Pro and Qwen3.5-122B-A10B
BenchmarkGemini 2.5 ProQwen3.5-122B-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 2.5 Pro$0.0063Fits 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 2.5 Pro$0.092Fits 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 2.5 Pro$0.350Fits 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 2.5 Pro and Qwen3.5-122B-A10B
SpecificationGoogle Gemini 2.5 ProQwen3.5-122B-A10B
MakerGoogleQwen
WeightsNo public weights listedOpen weights
ReleasedJune 17, 2025February 25, 2026
Context window1.05M262K
Input $/Mtok$1.25$0.26
Output $/Mtok$10.00$2.08
Coding index37.022.9
Independent measurements behind it21
Cost per solved task$0.64Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 2.5 Pro better than Qwen3.5-122B-A10B for coding?

Pick Gemini 2.5 Pro for coding: it scores 37.0 on the Vibe Coding Index against 22.9 for Qwen3.5-122B-A10B. Pick Qwen3.5-122B-A10B when output tokens cost 4.8x less, or when what matters is LMArena WebDev or AA Coding Index, where it leads.

Which is cheaper, Gemini 2.5 Pro or Qwen3.5-122B-A10B?

Gemini 2.5 Pro costs $1.25 per million input tokens and $10.00 per million output tokens; Qwen3.5-122B-A10B costs $0.26 and $2.08. Cost per solved task is known for Gemini 2.5 Pro only.

Which has the bigger context window, Gemini 2.5 Pro or Qwen3.5-122B-A10B?

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

How many benchmarks is the Gemini 2.5 Pro vs Qwen3.5-122B-A10B comparison based on?

49 benchmarks have a result for both models as of October 21, 2026. Gemini 2.5 Pro's coding index rests on 2 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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