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GPT-5.1-Codex-Mini vs Qwen3.7 Max

Qwen3.7 Max leads GPT-5.1-Codex-Mini on the Artificial Analysis Intelligence Index, 29.5 to 20.4, and GPT-5.1-Codex-Mini costs 2.2x less per output token ($2.00 vs $4.425 per million). Updated October 22, 2026; 17 benchmarks have a result for both.

Replace GPT-5.1-Codex-Mini Replace Qwen3.7 Max
GPT-5.1-Codex-MiniOpenAI
Coding
No data
Overall
No data
Output $/M
$2.00
0
Qwen3.7 MaxQwen
Coding
54.1
Overall
61.7
Output $/M
$4.425
17
vs boards won of 17 shared

GPT-5.1-Codex-Mini or Qwen3.7 Max: which to pick

Only Qwen3.7 Max has a coding score, 54.1 on the Vibe Coding Index; GPT-5.1-Codex-Mini has none, so the two cannot be ranked on coding.

Pick GPT-5.1-Codex-Mini for output tokens 2.2x cheaper ($2.00 vs $4.425 per million).

Model AGPT-5.1-Codex-MiniOpenAINot benchmarked1 independent benchmarkNo cost per solved taskModel BQwen3.7 MaxQwen54.1/1003 independent benchmarks$4.69 per solved task
Shared results
17
GPT-5.1-Codex-Mini only
5
Qwen3.7 Max only
42
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-5.1-Codex-Mini not benchmarked, Qwen3.7 Max 54.1 from 3 benchmarks.
Widest category
Coding, 33.1 points apart on average over 3 shared benchmarks.
Widest single gap
LMArena WebDev: HTML: GPT-5.1-Codex-Mini 1253 against Qwen3.7 Max 1512, 43.1 points apart on a 0 to 100 scale.
Output price
GPT-5.1-Codex-Mini $2.00 against Qwen3.7 Max $4.425 per million output tokens, 2.2x apart.
Context window
GPT-5.1-Codex-Mini takes 400K tokens, Qwen3.7 Max 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-5.1-Codex-MiniBarsQwen3.7 MaxTies
Coding03
Intelligence01
Agentic work01
Reasoning02
Web design08
General02
All shared boards017
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GPT-5.1-Codex-Mini and Qwen3.7 Max
BenchmarkGPT-5.1-Codex-MiniQwen3.7 MaxLeader
LMArena WebDev12441515Qwen3.7 Max
AA Coding IndexNot measured66.0Only Qwen3.7 Max measured
LiveCodeBench (Vals AI)Not measured87.1%Only Qwen3.7 Max measured
SWE-bench Verified (Vals AI)Not measured68.8%Only Qwen3.7 Max measured
Vibe Code Bench (Vals AI)Not measured47.7%Only Qwen3.7 Max measured
Code migration (Vals AI)Not measured13.1%Only Qwen3.7 Max measured
Terminal-Bench 2.1 (Vals AI)Not measured61.0%Only Qwen3.7 Max measured
LiveCodeBench (Artificial Analysis run)83.6%Not measuredOnly GPT-5.1-Codex-Mini measured
SciCodeNot measured49.5%Only Qwen3.7 Max measured
Terminal-Bench Hard (Artificial Analysis run)33.3%50.8%Qwen3.7 Max
Terminal-Bench61.6%Not measuredOnly GPT-5.1-Codex-Mini measured
ALE-BenchNot measured1189.4Only Qwen3.7 Max measured
LMArena WebDev: ReactNot measured1514Only Qwen3.7 Max measured
LMArena WebDev: HTML12531512Qwen3.7 Max
Neither model has a result on the other 25 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GPT-5.1-Codex-Mini and Qwen3.7 Max
BenchmarkGPT-5.1-Codex-MiniQwen3.7 MaxLeader
AA Intelligence Index20.429.5Qwen3.7 Max
Epoch Capabilities IndexNot measured154.0Only Qwen3.7 Max measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GPT-5.1-Codex-Mini and Qwen3.7 Max
BenchmarkGPT-5.1-Codex-MiniQwen3.7 MaxLeader
AA Agentic IndexNot measured22.5Only Qwen3.7 Max measured
Design Arena: agents building web appsNot measured1208Only Qwen3.7 Max measured
Design Arena: agents building full-stack appsNot measured1191Only Qwen3.7 Max measured
Design Arena: agents building mobile appsNot measured1155Only Qwen3.7 Max measured
Design Arena: agents building Android appsNot measured1159Only Qwen3.7 Max measured
Design Arena: agents building Godot gamesNot measured1187Only Qwen3.7 Max measured
Design Arena: agents building gamesNot measured1161Only Qwen3.7 Max measured
Design Arena: HTML slidesNot measured1108Only Qwen3.7 Max measured
Design Arena: PowerPoint slidesNot measured1171Only Qwen3.7 Max measured
Finance Agent (Vals AI)Not measured47.8%Only Qwen3.7 Max measured
Tax Agent Bench (Vals AI)Not measured15.8%Only Qwen3.7 Max measured
Legal Research Bench (Vals AI)Not measured25.5%Only Qwen3.7 Max measured
Excel Modeling Benchmark (Vals AI)Not measured57.0%Only Qwen3.7 Max measured
τ²-Bench Telecom62.9%94.7%Qwen3.7 Max
Neither model has a result on the other 27 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
Reasoning benchmarks for GPT-5.1-Codex-Mini and Qwen3.7 Max
BenchmarkGPT-5.1-Codex-MiniQwen3.7 MaxLeader
GPQA DiamondNot measured90.2%Only Qwen3.7 Max measured
GPQA Diamond (Artificial Analysis run)81.3%92.3%Qwen3.7 Max
Humanity's Last Exam (Artificial Analysis run)18.5%40.5%Qwen3.7 Max
GPQA Diamond (Epoch AI run)Not measured90.9%Only Qwen3.7 Max measured
SimpleBenchNot measured70.4%Only Qwen3.7 Max measured
Chess puzzlesNot measured26.0%Only Qwen3.7 Max measured
Mystery game puzzlesNot measured32.0%Only Qwen3.7 Max measured
EBR-benchNot measured9.5%Only Qwen3.7 Max measured
Neither model has a result on the other 14 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Math benchmarks for GPT-5.1-Codex-Mini and Qwen3.7 Max
BenchmarkGPT-5.1-Codex-MiniQwen3.7 MaxLeader
AA Math Index91.7Not measuredOnly GPT-5.1-Codex-Mini measured
AIME 2025 (Artificial Analysis run)91.7%Not measuredOnly GPT-5.1-Codex-Mini measured
OTIS Mock AIMENot measured95.6%Only Qwen3.7 Max measured
FrontierMath, tiers 1 to 3Not measured64.6%Only Qwen3.7 Max measured
FrontierMath, tier 4Not measured34.1%Only Qwen3.7 Max measured
ProofBenchNot measured26.0%Only Qwen3.7 Max measured
Neither model has a result on the other 7 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Knowledge benchmarks for GPT-5.1-Codex-Mini and Qwen3.7 Max
BenchmarkGPT-5.1-Codex-MiniQwen3.7 MaxLeader
MMLU ProNot measured89.3%Only Qwen3.7 Max measured
LegalBench (Vals AI)Not measured84.9%Only Qwen3.7 Max measured
CorpFin (Vals AI)Not measured63.7%Only Qwen3.7 Max measured
TaxEval (Vals AI)Not measured75.3%Only Qwen3.7 Max measured
MedCode (Vals AI)Not measured38.8%Only Qwen3.7 Max measured
MMLU Pro (Artificial Analysis run)82.0%Not measuredOnly GPT-5.1-Codex-Mini measured
SimpleQA VerifiedNot measured55.8%Only Qwen3.7 Max measured
Neither model has a result on the other 11 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index08
Web design benchmarks for GPT-5.1-Codex-Mini and Qwen3.7 Max
BenchmarkGPT-5.1-Codex-MiniQwen3.7 MaxLeader
Design Arena: websites11111274Qwen3.7 Max
Design Arena: UI components10781267Qwen3.7 Max
Design Arena: game dev10921264Qwen3.7 Max
Design Arena: data viz10971275Qwen3.7 Max
Design Arena: 3D9881265Qwen3.7 Max
Design Arena: all code categories10931275Qwen3.7 Max
Design Arena: SVG9781216Qwen3.7 Max
Design Arena: ASCII art11051211Qwen3.7 Max
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
General benchmarks for GPT-5.1-Codex-Mini and Qwen3.7 Max
BenchmarkGPT-5.1-Codex-MiniQwen3.7 MaxLeader
MedScribe (Vals AI)Not measured79.4%Only Qwen3.7 Max measured
IFBench67.9%80.5%Qwen3.7 Max
Long context reasoning (AA-LCR)66.7%79.0%Qwen3.7 Max
DTBenchNot measured92.3%Only Qwen3.7 Max measured
LMCANot measured44.0%Only Qwen3.7 Max measured
Neither model has a result on the other 41 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-5.1-Codex-Mini and Qwen3.7 Max
BenchmarkGPT-5.1-Codex-MiniQwen3.7 MaxLeader
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-5.1-Codex-Mini$0.0013Fits in one request
Qwen3.7 Max$0.0037Fits in one request

GPT-5.1-Codex-Mini costs less

Repository review

50K input + 3K output tokens

GPT-5.1-Codex-Mini$0.018Fits in one request
Qwen3.7 Max$0.087Fits in one request

GPT-5.1-Codex-Mini costs less

Agent loop

200K input + 10K output tokens

GPT-5.1-Codex-Mini$0.070Fits in one request
Qwen3.7 Max$0.339Fits in one request

GPT-5.1-Codex-Mini 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-5.1-Codex-Mini and Qwen3.7 Max
SpecificationOpenAI GPT-5.1-Codex-MiniQwen3.7 Max
MakerOpenAIQwen
WeightsNo public weights listedNo public weights listed
ReleasedNovember 13, 2025May 21, 2026
Context window400K1M
Input $/Mtok$0.25$1.475
Output $/Mtok$2.00$4.425
Coding indexNot benchmarked54.1
Independent measurements behind it13
Cost per solved taskNot computable$4.69
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-5.1-Codex-Mini better than Qwen3.7 Max for coding?

Only Qwen3.7 Max has a coding score, 54.1 on the Vibe Coding Index; GPT-5.1-Codex-Mini has none, so the two cannot be ranked on coding. Pick GPT-5.1-Codex-Mini for output tokens 2.2x cheaper ($2.00 vs $4.425 per million).

Which is cheaper, GPT-5.1-Codex-Mini or Qwen3.7 Max?

GPT-5.1-Codex-Mini costs $0.25 per million input tokens and $2.00 per million output tokens; Qwen3.7 Max costs $1.475 and $4.425. Cost per solved task is known for Qwen3.7 Max only.

Which has the bigger context window, GPT-5.1-Codex-Mini or Qwen3.7 Max?

Qwen3.7 Max, with 1M tokens against 400K.

How many benchmarks is the GPT-5.1-Codex-Mini vs Qwen3.7 Max comparison based on?

17 benchmarks have a result for both models as of October 22, 2026. GPT-5.1-Codex-Mini's coding index rests on 1 independent benchmark and Qwen3.7 Max's on 3. Where only one model has a result, the page says so instead of naming a winner.

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