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GPT-4o (2024-05-13) vs Qwen3.7 Plus

Qwen3.7 Plus leads GPT-4o (2024-05-13) on the Artificial Analysis Intelligence Index, 25.2 to 7.3, and Qwen3.7 Plus costs 11.7x less per output token ($1.28 vs $15.00 per million). Updated October 22, 2026; 37 benchmarks have a result for both.

Replace GPT-4o (2024-05-13) Replace Qwen3.7 Plus
GPT-4o (2024-05-13)OpenAI
Coding
No data
Overall
27.1
Output $/M
$15.00
0
Qwen3.7 PlusQwen
Coding
33.2
Overall
54.0
Output $/M
$1.28
37
vs boards won of 37 shared

GPT-4o (2024-05-13) or Qwen3.7 Plus: which to pick

Only Qwen3.7 Plus has a coding score, 33.2 on the Vibe Coding Index; GPT-4o (2024-05-13) has none, so the two cannot be ranked on coding.

Compare them on price, context and the boards below.

Model AGPT-4o (2024-05-13)OpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3.7 PlusQwen33.2/1002 independent benchmarksNo cost per solved task
Shared results
37
GPT-4o (2024-05-13) only
7
Qwen3.7 Plus only
38
Like-for-like categories
6 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 (2024-05-13) not benchmarked, Qwen3.7 Plus 33.2 from 2 benchmarks.
Widest category
Math, 49.5 points apart on average over 3 shared benchmarks.
Widest single gap
OTIS Mock AIME: GPT-4o (2024-05-13) 6.3% against Qwen3.7 Plus 93.3%, 87.1 points apart on a 0 to 100 scale.
Output price
GPT-4o (2024-05-13) $15.00 against Qwen3.7 Plus $1.28 per million output tokens, 11.7x apart.
Context window
GPT-4o (2024-05-13) 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 (2024-05-13)BarsQwen3.7 PlusTies
Coding03
Intelligence01
Reasoning06
Math03
Knowledge04
General020
All shared boards037
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GPT-4o (2024-05-13) and Qwen3.7 Plus
BenchmarkGPT-4o (2024-05-13)Qwen3.7 PlusLeader
AA Coding Index24.255.9Qwen3.7 Plus
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)33.4%Not measuredOnly GPT-4o (2024-05-13) measured
SciCodeNot measured46.1%Only Qwen3.7 Plus measured
Terminal-Bench Hard (Artificial Analysis run)Not measured47.0%Only Qwen3.7 Plus measured
FrontierCodeNot measured10.2%Only Qwen3.7 Plus measured
LMArena Text: coding12971473Qwen3.7 Plus
LMArena Text: software and IT12971473Qwen3.7 Plus
Neither model has a result on the other 32 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GPT-4o (2024-05-13) and Qwen3.7 Plus
BenchmarkGPT-4o (2024-05-13)Qwen3.7 PlusLeader
AA Intelligence Index7.325.2Qwen3.7 Plus
Epoch Capabilities IndexNot measured147.0Only Qwen3.7 Plus measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Agentic work benchmarks for GPT-4o (2024-05-13) and Qwen3.7 Plus
BenchmarkGPT-4o (2024-05-13)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 TelecomNot measured93.0%Only Qwen3.7 Plus measured
METR time horizons40.8%Not measuredOnly GPT-4o (2024-05-13) measured
OSWorld 2.0Not measured2.8%Only Qwen3.7 Plus measured
BALROG32.3%Not measuredOnly GPT-4o (2024-05-13) measured
Neither model has a result on the other 33 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
Reasoning benchmarks for GPT-4o (2024-05-13) and Qwen3.7 Plus
BenchmarkGPT-4o (2024-05-13)Qwen3.7 PlusLeader
GPQA Diamond50.2%Not measuredOnly GPT-4o (2024-05-13) measured
GPQA Diamond (Artificial Analysis run)52.6%90.0%Qwen3.7 Plus
Humanity's Last Exam (Artificial Analysis run)1.8%35.6%Qwen3.7 Plus
GPQA Diamond (Epoch AI run)48.9%87.9%Qwen3.7 Plus
Mystery game puzzlesNot measured17.0%Only Qwen3.7 Plus measured
LMArena Text: hard prompts12811460Qwen3.7 Plus
LMArena Text: expert12501466Qwen3.7 Plus
LMArena Text: hard prompts in English12931460Qwen3.7 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 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for GPT-4o (2024-05-13) and Qwen3.7 Plus
BenchmarkGPT-4o (2024-05-13)Qwen3.7 PlusLeader
OTIS Mock AIME6.3%93.3%Qwen3.7 Plus
FrontierMath, tiers 1 to 3Not measured34.4%Only Qwen3.7 Plus measured
MATH level 551.0%Not measuredOnly GPT-4o (2024-05-13) measured
LMArena Text: math12841467Qwen3.7 Plus
LMArena Text: mathematical work12841470Qwen3.7 Plus
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for GPT-4o (2024-05-13) and Qwen3.7 Plus
BenchmarkGPT-4o (2024-05-13)Qwen3.7 PlusLeader
MortgageTax (Vals AI)Not measured66.2%Only Qwen3.7 Plus measured
MMLU Pro (Artificial Analysis run)74.0%Not measuredOnly GPT-4o (2024-05-13) measured
MMLU84.2%Not measuredOnly GPT-4o (2024-05-13) measured
LMArena Text: science12951464Qwen3.7 Plus
LMArena Text: medicine and healthcare12781464Qwen3.7 Plus
LMArena Text: legal and government13141451Qwen3.7 Plus
LMArena Text: business and finance12621435Qwen3.7 Plus
Neither model has a result on the other 13 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for GPT-4o (2024-05-13) and Qwen3.7 Plus
BenchmarkGPT-4o (2024-05-13)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 index020
General benchmarks for GPT-4o (2024-05-13) and Qwen3.7 Plus
BenchmarkGPT-4o (2024-05-13)Qwen3.7 PlusLeader
SAGE (Vals AI)Not measured39.3%Only Qwen3.7 Plus measured
Vals Multimodal IndexNot measured53.9%Only Qwen3.7 Plus measured
IFBenchNot measured78.0%Only Qwen3.7 Plus measured
Long context reasoning (AA-LCR)Not measured73.0%Only Qwen3.7 Plus measured
DTBenchNot measured84.0%Only Qwen3.7 Plus measured
LMCANot measured37.6%Only Qwen3.7 Plus measured
LMArena Text13001454Qwen3.7 Plus
LMArena Text: instruction following12781439Qwen3.7 Plus
LMArena Text: creative writing12911438Qwen3.7 Plus
LMArena Vision11371278Qwen3.7 Plus
LMArena Text: English13121458Qwen3.7 Plus
LMArena Text: non-English12831445Qwen3.7 Plus
LMArena Text: Chinese12771509Qwen3.7 Plus
LMArena Text: German12831471Qwen3.7 Plus
LMArena Text: Japanese12571412Qwen3.7 Plus
LMArena Text: Korean12341413Qwen3.7 Plus
LMArena Text: French13041472Qwen3.7 Plus
LMArena Text: Spanish12921457Qwen3.7 Plus
LMArena Text: Russian12851457Qwen3.7 Plus
LMArena Text: Polish13651449Qwen3.7 Plus
LMArena Text: multi-turn13021459Qwen3.7 Plus
LMArena Text: longer queries12881454Qwen3.7 Plus
LMArena Text: writing and language12981437Qwen3.7 Plus
LMArena Text: entertainment and media12891422Qwen3.7 Plus
LMArena Vision: English11471280Qwen3.7 Plus
LMArena Vision: Chinese11321332Qwen3.7 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 (2024-05-13) and Qwen3.7 Plus
BenchmarkGPT-4o (2024-05-13)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 (2024-05-13)$0.013Fits 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 (2024-05-13)$0.295Fits 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 (2024-05-13)$1.15Exceeds 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 (2024-05-13) and Qwen3.7 Plus
SpecificationOpenAI GPT-4o (2024-05-13)Qwen3.7 Plus
MakerOpenAIQwen
WeightsNo public weights listedNo public weights listed
ReleasedMay 13, 2024June 3, 2026
Context window128K1M
Input $/Mtok$5.00$0.32
Output $/Mtok$15.00$1.28
Coding indexNot benchmarked33.2
Independent measurements behind it02
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4o (2024-05-13) better than Qwen3.7 Plus for coding?

Only Qwen3.7 Plus has a coding score, 33.2 on the Vibe Coding Index; GPT-4o (2024-05-13) has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

Which is cheaper, GPT-4o (2024-05-13) or Qwen3.7 Plus?

GPT-4o (2024-05-13) costs $5.00 per million input tokens and $15.00 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 (2024-05-13) or Qwen3.7 Plus?

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

How many benchmarks is the GPT-4o (2024-05-13) vs Qwen3.7 Plus comparison based on?

37 benchmarks have a result for both models as of October 22, 2026. GPT-4o (2024-05-13)'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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