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GPT-4o (2024-08-06) vs Qwen3.7 Plus

Qwen3.7 Plus leads GPT-4o (2024-08-06) on the Artificial Analysis Intelligence Index, 25.2 to 7.7, and Qwen3.7 Plus costs 7.8x less per output token ($1.28 vs $10.00 per million). Updated October 22, 2026; 41 benchmarks have a result for both.

Replace GPT-4o (2024-08-06) Replace Qwen3.7 Plus
GPT-4o (2024-08-06)OpenAI
Coding
No data
Overall
26.3
Output $/M
$10.00
0
Qwen3.7 PlusQwen
Coding
33.2
Overall
54.0
Output $/M
$1.28
41
vs boards won of 41 shared

GPT-4o (2024-08-06) or Qwen3.7 Plus: which to pick

Only Qwen3.7 Plus has a coding score, 33.2 on the Vibe Coding Index; GPT-4o (2024-08-06) has none, so the two cannot be ranked on coding.

Compare them on price, context and the boards below.

Model AGPT-4o (2024-08-06)OpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3.7 PlusQwen33.2/1002 independent benchmarksNo cost per solved task
Shared results
41
GPT-4o (2024-08-06) only
17
Qwen3.7 Plus only
34
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
GPT-4o (2024-08-06) not benchmarked, Qwen3.7 Plus 33.2 from 2 benchmarks.
Widest category
Agentic work, 64.0 points apart on average over 1 shared benchmark.
Widest single gap
OTIS Mock AIME: GPT-4o (2024-08-06) 6.4% against Qwen3.7 Plus 93.3%, 86.9 points apart on a 0 to 100 scale.
Output price
GPT-4o (2024-08-06) $10.00 against Qwen3.7 Plus $1.28 per million output tokens, 7.8x apart.
Context window
GPT-4o (2024-08-06) takes 128K 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
CategoryGPT-4o (2024-08-06)BarsQwen3.7 PlusTies
Coding03
Intelligence01
Agentic work01
Reasoning06
Math04
Knowledge05
General021
All shared boards041
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GPT-4o (2024-08-06) and Qwen3.7 Plus
BenchmarkGPT-4o (2024-08-06)Qwen3.7 PlusLeader
Aider polyglot23.1%Not measuredOnly GPT-4o (2024-08-06) measured
SWE-bench Lite21.7%Not measuredOnly GPT-4o (2024-08-06) measured
AA Coding IndexNot measured55.9Only Qwen3.7 Plus measured
Vibe Code Bench (Vals AI)Not measured46.4%Only Qwen3.7 Plus measured
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)31.7%Not measuredOnly GPT-4o (2024-08-06) measured
SciCodeNot measured46.1%Only Qwen3.7 Plus measured
Terminal-Bench Hard (Artificial Analysis run)8.3%47.0%Qwen3.7 Plus
FrontierCodeNot measured10.2%Only Qwen3.7 Plus measured
LMArena Text: coding12831473Qwen3.7 Plus
LMArena Text: software and IT12781473Qwen3.7 Plus
Neither model has a result on the other 30 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GPT-4o (2024-08-06) and Qwen3.7 Plus
BenchmarkGPT-4o (2024-08-06)Qwen3.7 PlusLeader
AA Intelligence Index7.725.2Qwen3.7 Plus
Epoch Capabilities IndexNot measured147.0Only Qwen3.7 Plus measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GPT-4o (2024-08-06) and Qwen3.7 Plus
BenchmarkGPT-4o (2024-08-06)Qwen3.7 PlusLeader
AA Agentic IndexNot measured17.5Only Qwen3.7 Plus measured
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 Telecom28.9%93.0%Qwen3.7 Plus
OSWorld 2.0Not measured2.8%Only Qwen3.7 Plus measured
Neither model has a result on the other 35 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
Reasoning benchmarks for GPT-4o (2024-08-06) and Qwen3.7 Plus
BenchmarkGPT-4o (2024-08-06)Qwen3.7 PlusLeader
MMMU Pro (Vals AI)64.0%Not measuredOnly GPT-4o (2024-08-06) measured
GPQA Diamond (Artificial Analysis run)52.1%90.0%Qwen3.7 Plus
Humanity's Last Exam (Artificial Analysis run)2.3%35.6%Qwen3.7 Plus
GPQA Diamond (Epoch AI run)49.2%87.9%Qwen3.7 Plus
SimpleBench17.8%Not measuredOnly GPT-4o (2024-08-06) measured
Chess puzzles6.0%Not measuredOnly GPT-4o (2024-08-06) measured
Mystery game puzzlesNot measured17.0%Only Qwen3.7 Plus measured
LMArena Text: hard prompts12641460Qwen3.7 Plus
LMArena Text: expert12411466Qwen3.7 Plus
LMArena Text: hard prompts in English12771460Qwen3.7 Plus
LMArena Vision: diagramsNot measured1292Only Qwen3.7 Plus measured
LMArena Vision: homeworkNot measured1295Only Qwen3.7 Plus measured
Neither model has a result on the other 11 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index04
Math benchmarks for GPT-4o (2024-08-06) and Qwen3.7 Plus
BenchmarkGPT-4o (2024-08-06)Qwen3.7 PlusLeader
AIME14.0%Not measuredOnly GPT-4o (2024-08-06) measured
MATH 500 (Vals AI)75.2%Not measuredOnly GPT-4o (2024-08-06) measured
MGSM (Vals AI)90.7%Not measuredOnly GPT-4o (2024-08-06) measured
OTIS Mock AIME6.4%93.3%Qwen3.7 Plus
FrontierMath, tiers 1 to 30.4%34.4%Qwen3.7 Plus
MATH level 553.3%Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: math12851467Qwen3.7 Plus
LMArena Text: mathematical work12831470Qwen3.7 Plus
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
Knowledge benchmarks for GPT-4o (2024-08-06) and Qwen3.7 Plus
BenchmarkGPT-4o (2024-08-06)Qwen3.7 PlusLeader
MMLU Pro74.1%Not measuredOnly GPT-4o (2024-08-06) measured
LegalBench (Vals AI)80.1%Not measuredOnly GPT-4o (2024-08-06) measured
CorpFin (Vals AI)39.4%Not measuredOnly GPT-4o (2024-08-06) measured
TaxEval (Vals AI)71.1%Not measuredOnly GPT-4o (2024-08-06) measured
MortgageTax (Vals AI)61.0%66.2%Qwen3.7 Plus
MedQA (Vals AI)88.2%Not measuredOnly GPT-4o (2024-08-06) measured
SimpleQA Verified26.0%Not measuredOnly GPT-4o (2024-08-06) measured
MMLU84.3%Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: science12741464Qwen3.7 Plus
LMArena Text: medicine and healthcare12521464Qwen3.7 Plus
LMArena Text: legal and government12751451Qwen3.7 Plus
LMArena Text: business and finance12321435Qwen3.7 Plus
Neither model has a result on the other 8 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for GPT-4o (2024-08-06) and Qwen3.7 Plus
BenchmarkGPT-4o (2024-08-06)Qwen3.7 PlusLeader
Design Arena: websitesNot measured1269Only Qwen3.7 Plus measured
Design Arena: UI componentsNot measured1258Only Qwen3.7 Plus measured
Design Arena: game devNot measured1262Only Qwen3.7 Plus measured
Design Arena: data vizNot measured1277Only Qwen3.7 Plus measured
Design Arena: 3DNot measured1238Only Qwen3.7 Plus measured
Design Arena: all code categoriesNot measured1268Only Qwen3.7 Plus measured
Design Arena: SVGNot measured1207Only 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 index021
General benchmarks for GPT-4o (2024-08-06) and Qwen3.7 Plus
BenchmarkGPT-4o (2024-08-06)Qwen3.7 PlusLeader
SAGE (Vals AI)Not measured39.3%Only Qwen3.7 Plus measured
Vals Multimodal IndexNot measured53.9%Only Qwen3.7 Plus measured
IFBench36.0%78.0%Qwen3.7 Plus
Long context reasoning (AA-LCR)41.0%73.0%Qwen3.7 Plus
DTBenchNot measured84.0%Only Qwen3.7 Plus measured
LMCANot measured37.6%Only Qwen3.7 Plus measured
LMArena Text12831454Qwen3.7 Plus
LMArena Text: instruction following12671439Qwen3.7 Plus
LMArena Text: creative writing12741438Qwen3.7 Plus
LMArena Vision10651278Qwen3.7 Plus
LMArena Text: English12971458Qwen3.7 Plus
LMArena Text: non-English12621445Qwen3.7 Plus
LMArena Text: Chinese12541509Qwen3.7 Plus
LMArena Text: German12571471Qwen3.7 Plus
LMArena Text: Japanese12341412Qwen3.7 Plus
LMArena Text: Korean12181413Qwen3.7 Plus
LMArena Text: French12631472Qwen3.7 Plus
LMArena Text: Spanish12691457Qwen3.7 Plus
LMArena Text: Russian12721457Qwen3.7 Plus
LMArena Text: PolishNot measured1449Only Qwen3.7 Plus measured
LMArena Text: multi-turn12791459Qwen3.7 Plus
LMArena Text: longer queries12831454Qwen3.7 Plus
LMArena Text: writing and language12901437Qwen3.7 Plus
LMArena Text: entertainment and media12671422Qwen3.7 Plus
LMArena Vision: English10721280Qwen3.7 Plus
LMArena Vision: Chinese10091332Qwen3.7 Plus
LMArena Vision: reading textNot measured1288Only Qwen3.7 Plus measured
LMArena Vision: humorNot measured1261Only Qwen3.7 Plus measured
LMArena Vision: creative writingNot measured1258Only Qwen3.7 Plus measured
LMArena DocumentNot measured1444Only Qwen3.7 Plus measured
Neither model has a result on the other 18 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-4o (2024-08-06) and Qwen3.7 Plus
BenchmarkGPT-4o (2024-08-06)Qwen3.7 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

GPT-4o (2024-08-06)$0.0075Fits in one request
Qwen3.7 Plus$0.0010Fits in one request

Qwen3.7 Plus costs less

Repository review

50K input + 3K output tokens

GPT-4o (2024-08-06)$0.155Fits in one request
Qwen3.7 Plus$0.020Fits in one request

Qwen3.7 Plus costs less

Agent loop

200K input + 10K output tokens

GPT-4o (2024-08-06)$0.600Exceeds the context window
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 GPT-4o (2024-08-06) and Qwen3.7 Plus
SpecificationOpenAI GPT-4o (2024-08-06)Qwen3.7 Plus
MakerOpenAIQwen
WeightsNo public weights listedNo public weights listed
ReleasedAugust 6, 2024June 3, 2026
Context window128K1M
Input $/Mtok$2.50$0.32
Output $/Mtok$10.00$1.28
Coding indexNot benchmarked33.2
Independent measurements behind it02
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4o (2024-08-06) better than Qwen3.7 Plus for coding?

Only Qwen3.7 Plus has a coding score, 33.2 on the Vibe Coding Index; GPT-4o (2024-08-06) has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

Which is cheaper, GPT-4o (2024-08-06) or Qwen3.7 Plus?

GPT-4o (2024-08-06) costs $2.50 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 neither of them.

Which has the bigger context window, GPT-4o (2024-08-06) or Qwen3.7 Plus?

Qwen3.7 Plus, with 1M tokens against 128K.

How many benchmarks is the GPT-4o (2024-08-06) vs Qwen3.7 Plus comparison based on?

41 benchmarks have a result for both models as of October 22, 2026. GPT-4o (2024-08-06)'s coding index rests on 0 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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