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Gemini 2.5 Pro vs Qwen3.7 Plus

Qwen3.7 Plus leads Gemini 2.5 Pro on coding, 33.2 to 19.1 on the Vibe Coding Index, and Qwen3.7 Plus costs 7.8x less per output token ($1.28 vs $10.00 per million). Updated October 21, 2026; 62 benchmarks have a result for both.

Replace Gemini 2.5 Pro Replace Qwen3.7 Plus
Gemini 2.5 ProGoogle
Coding
19.1
Overall
41.8
Output $/M
$10.00
21
Qwen3.7 PlusQwen
Coding
33.2
Overall
54.0
Output $/M
$1.28
41
vs boards won of 62 shared

Gemini 2.5 Pro or Qwen3.7 Plus: which to pick

Pick Qwen3.7 Plus for coding: it scores 33.2 on the Vibe Coding Index against 19.1 for Gemini 2.5 Pro, though on 2 benchmarks against 3.

Pick Gemini 2.5 Pro for a larger context window (1.05M against 1M tokens) and work measured by SciCode or MortgageTax (Vals AI), where it leads.

Model AGemini 2.5 ProGoogle19.1/1003 independent benchmarks$0.64 per solved taskModel BQwen3.7 PlusQwen33.2/1002 independent benchmarksNo cost per solved task
Shared results
62
Gemini 2.5 Pro only
28
Qwen3.7 Plus only
13
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, Qwen3.7 Plus 33.2 from 2 benchmarks.
Widest category
Agentic work, 27.4 points apart on average over 2 shared benchmarks.
Widest single gap
Vibe Code Bench (Vals AI): Gemini 2.5 Pro 0.4% against Qwen3.7 Plus 46.4%, 46.0 points apart on a 0 to 100 scale.
Output price
Gemini 2.5 Pro $10.00 against Qwen3.7 Plus $1.28 per million output tokens, 7.8x apart.
Context window
Gemini 2.5 Pro takes 1.05M tokens, Qwen3.7 Plus 1M.

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 ProBarsQwen3.7 PlusTies
Coding15
Intelligence02
Agentic work02
Reasoning08
Math04
Knowledge50
Web design06
General1514
All shared boards2141
CodingLike-for-likeSix of these boards feed the Vibe Coding Index15
Coding benchmarks for Gemini 2.5 Pro and Qwen3.7 Plus
BenchmarkGemini 2.5 ProQwen3.7 PlusLeader
SWE-bench Verified53.6%Not measuredOnly Gemini 2.5 Pro measured
LMArena WebDev1226Not measuredOnly Gemini 2.5 Pro measured
AA Coding Index33.355.9Qwen3.7 Plus
SWE-bench Verified (Vals AI)54.4%Not measuredOnly Gemini 2.5 Pro measured
Vibe Code Bench (Vals AI)0.4%46.4%Qwen3.7 Plus
Code migration (Vals AI)Not measured12.9%Only Qwen3.7 Plus measured
Terminal-Bench 2.1 (Vals AI)Not measured52.8%Only Qwen3.7 Plus measured
SkillsBench (Vals AI)Not measured54.3%Only Qwen3.7 Plus measured
LiveCodeBench (Artificial Analysis run)80.1%Not measuredOnly Gemini 2.5 Pro measured
SciCode46.3%46.1%Gemini 2.5 Pro
Terminal-Bench Hard (Artificial Analysis run)26.5%47.0%Qwen3.7 Plus
Terminal-Bench32.6%Not measuredOnly Gemini 2.5 Pro measured
FrontierCodeNot measured10.2%Only Qwen3.7 Plus measured
GSO-Bench3.9%Not measuredOnly Gemini 2.5 Pro measured
WeirdML54.0%Not measuredOnly Gemini 2.5 Pro measured
LMArena Text: coding14521473Qwen3.7 Plus
LMArena Text: software and IT14591473Qwen3.7 Plus
LMArena WebDev: HTML1235Not measuredOnly Gemini 2.5 Pro measured
LMArena WebDev: from an image1285Not measuredOnly Gemini 2.5 Pro measured
Neither model has a result on the other 20 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Gemini 2.5 Pro and Qwen3.7 Plus
BenchmarkGemini 2.5 ProQwen3.7 PlusLeader
AA Intelligence Index16.125.2Qwen3.7 Plus
Epoch Capabilities Index145.1147.0Qwen3.7 Plus
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
Agentic work benchmarks for Gemini 2.5 Pro and Qwen3.7 Plus
BenchmarkGemini 2.5 ProQwen3.7 PlusLeader
AA Agentic Index1.617.5Qwen3.7 Plus
Finance Agent (Vals AI)Not measured38.2%Only Qwen3.7 Plus measured
Tax Agent Bench (Vals AI)Not measured10.5%Only Qwen3.7 Plus measured
Legal Research Bench (Vals AI)Not measured16.4%Only Qwen3.7 Plus measured
Excel Modeling Benchmark (Vals AI)Not measured49.3%Only Qwen3.7 Plus measured
τ²-Bench Telecom54.1%93.0%Qwen3.7 Plus
GDPval23.3%Not measuredOnly Gemini 2.5 Pro measured
OSWorld 2.0Not measured2.8%Only Qwen3.7 Plus 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 30 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index08
Reasoning benchmarks for Gemini 2.5 Pro and Qwen3.7 Plus
BenchmarkGemini 2.5 ProQwen3.7 PlusLeader
GPQA Diamond (Artificial Analysis run)84.4%90.0%Qwen3.7 Plus
Humanity's Last Exam (Artificial Analysis run)22.5%35.6%Qwen3.7 Plus
GPQA Diamond (Epoch AI run)85.3%87.9%Qwen3.7 Plus
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 Qwen3.7 Plus measured
LMArena Text: hard prompts14551460Qwen3.7 Plus
LMArena Text: expert14521466Qwen3.7 Plus
LMArena Text: hard prompts in English14531460Qwen3.7 Plus
LMArena Vision: diagrams12741292Qwen3.7 Plus
LMArena Vision: homework12811295Qwen3.7 Plus
Kagi LLM Benchmark70.3%Not measuredOnly Gemini 2.5 Pro measured
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index04
Math benchmarks for Gemini 2.5 Pro and Qwen3.7 Plus
BenchmarkGemini 2.5 ProQwen3.7 PlusLeader
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%93.3%Qwen3.7 Plus
FrontierMath, tiers 1 to 324.6%34.4%Qwen3.7 Plus
FrontierMath, tier 40.0%Not measuredOnly Gemini 2.5 Pro measured
LMArena Text: math14501467Qwen3.7 Plus
LMArena Text: mathematical work14541470Qwen3.7 Plus
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index50
Knowledge benchmarks for Gemini 2.5 Pro and Qwen3.7 Plus
BenchmarkGemini 2.5 ProQwen3.7 PlusLeader
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%66.2%Gemini 2.5 Pro
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: science14801464Gemini 2.5 Pro
LMArena Text: medicine and healthcare14761464Gemini 2.5 Pro
LMArena Text: legal and government14801451Gemini 2.5 Pro
LMArena Text: business and finance14391435Gemini 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 designLike-for-likePublic boards, shown as published, kept out of the index06
Web design benchmarks for Gemini 2.5 Pro and Qwen3.7 Plus
BenchmarkGemini 2.5 ProQwen3.7 PlusLeader
Design Arena: websites11671269Qwen3.7 Plus
Design Arena: UI components11401261Qwen3.7 Plus
Design Arena: game dev11111262Qwen3.7 Plus
Design Arena: data viz12211276Qwen3.7 Plus
Design Arena: 3D10811239Qwen3.7 Plus
Design Arena: all code categories11521269Qwen3.7 Plus
Design Arena: SVGNot measured1208Only Qwen3.7 Plus measured
Design Arena: ASCII artNot measured1143Only Qwen3.7 Plus measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index1514
General benchmarks for Gemini 2.5 Pro and Qwen3.7 Plus
BenchmarkGemini 2.5 ProQwen3.7 PlusLeader
SAGE (Vals AI)41.9%39.3%Gemini 2.5 Pro
MedScribe (Vals AI)73.5%Not measuredOnly Gemini 2.5 Pro measured
Vals Multimodal IndexNot measured53.9%Only Qwen3.7 Plus measured
IFBench48.7%78.0%Qwen3.7 Plus
Long context reasoning (AA-LCR)69.0%73.0%Qwen3.7 Plus
DTBench82.4%84.0%Qwen3.7 Plus
LMCA34.8%37.6%Qwen3.7 Plus
Creative writing (Lech Mazur)83.8%Not measuredOnly Gemini 2.5 Pro measured
LMArena Text14581454Gemini 2.5 Pro
LMArena Text: instruction following14371439Qwen3.7 Plus
LMArena Text: creative writing14541438Gemini 2.5 Pro
LMArena Vision12631278Qwen3.7 Plus
LMArena Text: English14581458Qwen3.7 Plus
LMArena Text: non-English14521445Gemini 2.5 Pro
LMArena Text: Chinese15071509Qwen3.7 Plus
LMArena Text: German14871471Gemini 2.5 Pro
LMArena Text: Japanese14611412Gemini 2.5 Pro
LMArena Text: Korean14341413Gemini 2.5 Pro
LMArena Text: French14731472Gemini 2.5 Pro
LMArena Text: Spanish14741457Gemini 2.5 Pro
LMArena Text: Russian14611457Gemini 2.5 Pro
LMArena Text: Polish14791449Gemini 2.5 Pro
LMArena Text: multi-turn14531459Qwen3.7 Plus
LMArena Text: longer queries14491454Qwen3.7 Plus
LMArena Text: writing and language14541437Gemini 2.5 Pro
LMArena Text: entertainment and media14411422Gemini 2.5 Pro
LMArena Vision: English12611280Qwen3.7 Plus
LMArena Vision: Chinese13001332Qwen3.7 Plus
LMArena Vision: reading text12701288Qwen3.7 Plus
LMArena Vision: humor12621261Gemini 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 writing12651258Gemini 2.5 Pro
LMArena Document14211444Qwen3.7 Plus
Neither model has a result on the other 12 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 Qwen3.7 Plus
BenchmarkGemini 2.5 ProQwen3.7 PlusLeader
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
Qwen3.7 Plus$0.0010Fits in one request

Qwen3.7 Plus costs less

Repository review

50K input + 3K output tokens

Gemini 2.5 Pro$0.092Fits in one request
Qwen3.7 Plus$0.020Fits in one request

Qwen3.7 Plus costs less

Agent loop

200K input + 10K output tokens

Gemini 2.5 Pro$0.350Fits in one request
Qwen3.7 Plus$0.077Fits in one request

Qwen3.7 Plus 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 Qwen3.7 Plus
SpecificationGoogle Gemini 2.5 ProQwen3.7 Plus
MakerGoogleQwen
WeightsNo public weights listedNo public weights listed
ReleasedJune 17, 2025June 3, 2026
Context window1.05M1M
Input $/Mtok$1.25$0.32
Output $/Mtok$10.00$1.28
Coding index19.133.2
Independent measurements behind it32
Cost per solved task$0.64Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 2.5 Pro better than Qwen3.7 Plus for coding?

Pick Qwen3.7 Plus for coding: it scores 33.2 on the Vibe Coding Index against 19.1 for Gemini 2.5 Pro, though on 2 benchmarks against 3. Pick Gemini 2.5 Pro for a larger context window (1.05M against 1M tokens) and work measured by SciCode or MortgageTax (Vals AI), where it leads.

Which is cheaper, Gemini 2.5 Pro or Qwen3.7 Plus?

Gemini 2.5 Pro costs $1.25 per million input tokens and $10.00 per million output tokens; Qwen3.7 Plus costs $0.32 and $1.28. Cost per solved task is known for Gemini 2.5 Pro only.

Which has the bigger context window, Gemini 2.5 Pro or Qwen3.7 Plus?

Gemini 2.5 Pro, with 1.05M tokens against 1M.

How many benchmarks is the Gemini 2.5 Pro vs Qwen3.7 Plus comparison based on?

62 benchmarks have a result for both models as of October 21, 2026. Gemini 2.5 Pro's coding index rests on 3 independent benchmarks and Qwen3.7 Plus's on 2. Where only one model has a result, the page says so instead of naming a winner.

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<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/gemini-2-5-pro-vs-qwen3-7-plus">LLMBenchmark.ai, Gemini 2.5 Pro vs Qwen3.7 Plus</a></p>