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Gemini 2.5 Pro vs Qwen3.5-27B

Qwen3.5-27B leads Gemini 2.5 Pro on the Artificial Analysis Intelligence Index, 22.9 to 16.1, and Qwen3.5-27B costs 6.4x less per output token ($1.56 vs $10.00 per million). Updated October 22, 2026; 51 benchmarks have a result for both.

Replace Gemini 2.5 Pro Replace Qwen3.5-27B
Gemini 2.5 ProGoogle
Coding
19.1
Overall
41.8
Output $/M
$10.00
40
Qwen3.5-27BQwen
Coding
No data
Overall
No data
Output $/M
$1.56
10
vs boards won of 51 shared, 1 tied

Gemini 2.5 Pro or Qwen3.5-27B: which to pick

Only Gemini 2.5 Pro has a coding score, 19.1 on the Vibe Coding Index; Qwen3.5-27B has none, so the two cannot be ranked on coding.

Pick Qwen3.5-27B for output tokens 6.4x cheaper ($1.56 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 BQwen3.5-27BQwenNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
51
Gemini 2.5 Pro only
39
Qwen3.5-27B only
2
Like-for-like categories
7 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, Qwen3.5-27B not benchmarked.
Widest category
Agentic work, 21.0 points apart on average over 2 shared benchmarks.
Widest single gap
τ²-Bench Telecom: Gemini 2.5 Pro 54.1% against Qwen3.5-27B 93.9%, 39.8 points apart on a 0 to 100 scale.
Output price
Gemini 2.5 Pro $10.00 against Qwen3.5-27B $1.56 per million output tokens, 6.4x apart.
Context window
Gemini 2.5 Pro takes 1.05M tokens, Qwen3.5-27B 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 ProBarsQwen3.5-27BTies
Coding33
Intelligence01
Agentic work11
Reasoning52
Math20
Knowledge40
General2531 tie
All shared boards40101 tie
CodingLike-for-likeSix of these boards feed the Vibe Coding Index33
Coding benchmarks for Gemini 2.5 Pro and Qwen3.5-27B
BenchmarkGemini 2.5 ProQwen3.5-27BLeader
SWE-bench Verified53.6%Not measuredOnly Gemini 2.5 Pro measured
LMArena WebDev12261358Qwen3.5-27B
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%Not measuredOnly Gemini 2.5 Pro measured
Terminal-Bench Hard (Artificial Analysis run)26.5%32.6%Qwen3.5-27B
Terminal-Bench32.6%Not measuredOnly Gemini 2.5 Pro measured
GSO-Bench3.9%Not measuredOnly Gemini 2.5 Pro measured
WeirdML54.0%39.5%Gemini 2.5 Pro
ALE-BenchNot measured349.4Only Qwen3.5-27B measured
LMArena Text: coding14521427Gemini 2.5 Pro
LMArena Text: software and IT14591431Gemini 2.5 Pro
LMArena WebDev: ReactNot measured1346Only Qwen3.5-27B measured
LMArena WebDev: HTML12351386Qwen3.5-27B
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 Qwen3.5-27B
BenchmarkGemini 2.5 ProQwen3.5-27BLeader
AA Intelligence Index16.122.9Qwen3.5-27B
Epoch Capabilities Index145.1Not measuredOnly Gemini 2.5 Pro measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index11
Agentic work benchmarks for Gemini 2.5 Pro and Qwen3.5-27B
BenchmarkGemini 2.5 ProQwen3.5-27BLeader
AA Agentic Index1.6Not measuredOnly Gemini 2.5 Pro measured
τ²-Bench Telecom54.1%93.9%Qwen3.5-27B
GDPval23.3%Not measuredOnly Gemini 2.5 Pro measured
DeepResearch Bench41.5%Not measuredOnly Gemini 2.5 Pro measured
Vending-Bench 2$574$202Gemini 2.5 Pro
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 index52
Reasoning benchmarks for Gemini 2.5 Pro and Qwen3.5-27B
BenchmarkGemini 2.5 ProQwen3.5-27BLeader
GPQA Diamond (Artificial Analysis run)84.4%85.8%Qwen3.5-27B
Humanity's Last Exam (Artificial Analysis run)22.5%23.9%Qwen3.5-27B
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
LMArena Text: hard prompts14551415Gemini 2.5 Pro
LMArena Text: expert14521427Gemini 2.5 Pro
LMArena Text: hard prompts in English14531429Gemini 2.5 Pro
LMArena Vision: diagrams12741249Gemini 2.5 Pro
LMArena Vision: homework12811256Gemini 2.5 Pro
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 index20
Math benchmarks for Gemini 2.5 Pro and Qwen3.5-27B
BenchmarkGemini 2.5 ProQwen3.5-27BLeader
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: math14501429Gemini 2.5 Pro
LMArena Text: mathematical work14541429Gemini 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 Qwen3.5-27B
BenchmarkGemini 2.5 ProQwen3.5-27BLeader
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: science14801437Gemini 2.5 Pro
LMArena Text: medicine and healthcare14761425Gemini 2.5 Pro
LMArena Text: legal and government14801405Gemini 2.5 Pro
LMArena Text: business and finance14391399Gemini 2.5 Pro
FACTS Benchmark Suite61.5%Not measuredOnly Gemini 2.5 Pro measured
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 Qwen3.5-27B
BenchmarkGemini 2.5 ProQwen3.5-27BLeader
Design Arena: websites1167Not measuredOnly Gemini 2.5 Pro measured
Design Arena: UI components1137Not measuredOnly Gemini 2.5 Pro measured
Design Arena: game dev1111Not 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 index253
General benchmarks for Gemini 2.5 Pro and Qwen3.5-27B
BenchmarkGemini 2.5 ProQwen3.5-27BLeader
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%75.6%Qwen3.5-27B
Long context reasoning (AA-LCR)69.0%77.7%Qwen3.5-27B
DTBench82.4%82.4%Tie
LMCA34.8%34.0%Gemini 2.5 Pro
Creative writing (Lech Mazur)83.8%Not measuredOnly Gemini 2.5 Pro measured
LMArena Text14581409Gemini 2.5 Pro
LMArena Text: instruction following14371393Gemini 2.5 Pro
LMArena Text: creative writing14541362Gemini 2.5 Pro
LMArena Vision12631241Gemini 2.5 Pro
LMArena Text: English14581425Gemini 2.5 Pro
LMArena Text: non-English14521390Gemini 2.5 Pro
LMArena Text: Chinese15071478Gemini 2.5 Pro
LMArena Text: German14871392Gemini 2.5 Pro
LMArena Text: Japanese14611346Gemini 2.5 Pro
LMArena Text: Korean14341359Gemini 2.5 Pro
LMArena Text: French14731410Gemini 2.5 Pro
LMArena Text: Spanish14741407Gemini 2.5 Pro
LMArena Text: Russian14611390Gemini 2.5 Pro
LMArena Text: Polish14791375Gemini 2.5 Pro
LMArena Text: multi-turn14531410Gemini 2.5 Pro
LMArena Text: longer queries14491413Gemini 2.5 Pro
LMArena Text: writing and language14541380Gemini 2.5 Pro
LMArena Text: entertainment and media14411363Gemini 2.5 Pro
LMArena Vision: English12611246Gemini 2.5 Pro
LMArena Vision: Chinese13001301Qwen3.5-27B
LMArena Vision: reading text12701246Gemini 2.5 Pro
LMArena Vision: humor12621227Gemini 2.5 Pro
LMArena Vision: captioning13041170Gemini 2.5 Pro
LMArena Vision: recognizing things12831210Gemini 2.5 Pro
LMArena Vision: creative writing12651224Gemini 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 Qwen3.5-27B
BenchmarkGemini 2.5 ProQwen3.5-27BLeader
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
Qwen3.5-27B$0.0010Fits in one request

Qwen3.5-27B costs less

Repository review

50K input + 3K output tokens

Gemini 2.5 Pro$0.092Fits in one request
Qwen3.5-27B$0.014Fits in one request

Qwen3.5-27B costs less

Agent loop

200K input + 10K output tokens

Gemini 2.5 Pro$0.350Fits in one request
Qwen3.5-27B$0.055Fits in one request

Qwen3.5-27B 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 Qwen3.5-27B
SpecificationGoogle Gemini 2.5 ProQwen3.5-27B
MakerGoogleQwen
WeightsNo public weights listedOpen weights
ReleasedJune 17, 2025February 25, 2026
Context window1.05M262K
Input $/Mtok$1.25$0.195
Output $/Mtok$10.00$1.56
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 Qwen3.5-27B for coding?

Only Gemini 2.5 Pro has a coding score, 19.1 on the Vibe Coding Index; Qwen3.5-27B has none, so the two cannot be ranked on coding. Pick Qwen3.5-27B for output tokens 6.4x cheaper ($1.56 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 Qwen3.5-27B?

Gemini 2.5 Pro costs $1.25 per million input tokens and $10.00 per million output tokens; Qwen3.5-27B costs $0.195 and $1.56. Cost per solved task is known for Gemini 2.5 Pro only.

Which has the bigger context window, Gemini 2.5 Pro or Qwen3.5-27B?

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

How many benchmarks is the Gemini 2.5 Pro vs Qwen3.5-27B comparison based on?

51 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 Qwen3.5-27B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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