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GPT-5.1-Codex-Mini vs Qwen3.5 397B A17B

Qwen3.5 397B A17B leads GPT-5.1-Codex-Mini on the Artificial Analysis Intelligence Index, 21.4 to 20.4, at about the same output price ($2.34 vs $2.00 per million). Updated October 22, 2026; 16 benchmarks have a result for both.

Replace GPT-5.1-Codex-Mini Replace Qwen3.5 397B A17B
GPT-5.1-Codex-MiniOpenAI
Coding
No data
Overall
No data
Output $/M
$2.00
0
Qwen3.5 397B A17BQwen
Coding
No data
Overall
57.1
Output $/M
$2.34
16
vs boards won of 16 shared

GPT-5.1-Codex-Mini or Qwen3.5 397B A17B: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick GPT-5.1-Codex-Mini for output tokens 1.2x cheaper ($2.00 vs $2.34 per million) and a larger context window (400K against 262K tokens).

Model AGPT-5.1-Codex-MiniOpenAINot benchmarked1 independent benchmarkNo cost per solved taskModel BQwen3.5 397B A17BQwenNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
16
GPT-5.1-Codex-Mini only
6
Qwen3.5 397B A17B only
49
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, Qwen3.5 397B A17B not benchmarked.
Widest category
Agentic work, 32.7 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GPT-5.1-Codex-Mini 62.9% against Qwen3.5 397B A17B 95.6%, 32.7 points apart on a 0 to 100 scale.
Output price
GPT-5.1-Codex-Mini $2.00 against Qwen3.5 397B A17B $2.34 per million output tokens, 1.2x apart.
Context window
GPT-5.1-Codex-Mini takes 400K tokens, Qwen3.5 397B A17B 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
CategoryGPT-5.1-Codex-MiniBarsQwen3.5 397B A17BTies
Coding03
Intelligence01
Agentic work01
Reasoning02
Web design07
General02
All shared boards016
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GPT-5.1-Codex-Mini and Qwen3.5 397B A17B
BenchmarkGPT-5.1-Codex-MiniQwen3.5 397B A17BLeader
LMArena WebDev12441400Qwen3.5 397B A17B
LiveCodeBench (Artificial Analysis run)83.6%Not measuredOnly GPT-5.1-Codex-Mini measured
SciCodeNot measured44.8%Only Qwen3.5 397B A17B measured
Terminal-Bench Hard (Artificial Analysis run)33.3%40.9%Qwen3.5 397B A17B
Terminal-Bench61.6%Not measuredOnly GPT-5.1-Codex-Mini measured
ALE-BenchNot measured621.9Only Qwen3.5 397B A17B measured
LMArena Text: codingNot measured1464Only Qwen3.5 397B A17B measured
LMArena Text: software and ITNot measured1463Only Qwen3.5 397B A17B measured
LMArena WebDev: ReactNot measured1388Only Qwen3.5 397B A17B measured
LMArena WebDev: HTML12531410Qwen3.5 397B A17B
Neither model has a result on the other 29 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GPT-5.1-Codex-Mini and Qwen3.5 397B A17B
BenchmarkGPT-5.1-Codex-MiniQwen3.5 397B A17BLeader
AA Intelligence Index20.421.4Qwen3.5 397B A17B
Epoch Capabilities IndexNot measured146.8Only Qwen3.5 397B A17B measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GPT-5.1-Codex-Mini and Qwen3.5 397B A17B
BenchmarkGPT-5.1-Codex-MiniQwen3.5 397B A17BLeader
τ²-Bench Telecom62.9%95.6%Qwen3.5 397B A17B
APEX-AgentsNot measured24.9%Only Qwen3.5 397B A17B measured
Neither model has a result on the other 39 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
Reasoning benchmarks for GPT-5.1-Codex-Mini and Qwen3.5 397B A17B
BenchmarkGPT-5.1-Codex-MiniQwen3.5 397B A17BLeader
GPQA Diamond (Artificial Analysis run)81.3%89.3%Qwen3.5 397B A17B
Humanity's Last Exam (Artificial Analysis run)18.5%29.0%Qwen3.5 397B A17B
GPQA Diamond (Epoch AI run)Not measured86.4%Only Qwen3.5 397B A17B measured
Mystery game puzzlesNot measured18.0%Only Qwen3.5 397B A17B measured
LMArena Text: hard promptsNot measured1448Only Qwen3.5 397B A17B measured
LMArena Text: expertNot measured1462Only Qwen3.5 397B A17B measured
LMArena Text: hard prompts in EnglishNot measured1450Only Qwen3.5 397B A17B measured
LMArena Vision: diagramsNot measured1277Only Qwen3.5 397B A17B measured
LMArena Vision: homeworkNot measured1292Only Qwen3.5 397B A17B measured
Neither model has a result on the other 13 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 Qwen3.5 397B A17B
BenchmarkGPT-5.1-Codex-MiniQwen3.5 397B A17BLeader
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 measured88.9%Only Qwen3.5 397B A17B measured
FrontierMath, tiers 1 to 3Not measured31.2%Only Qwen3.5 397B A17B measured
LMArena Text: mathNot measured1453Only Qwen3.5 397B A17B measured
LMArena Text: mathematical workNot measured1454Only Qwen3.5 397B A17B measured
Neither model has a result on the other 7 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Knowledge benchmarks for GPT-5.1-Codex-Mini and Qwen3.5 397B A17B
BenchmarkGPT-5.1-Codex-MiniQwen3.5 397B A17BLeader
MMLU Pro (Artificial Analysis run)82.0%Not measuredOnly GPT-5.1-Codex-Mini measured
LMArena Text: scienceNot measured1457Only Qwen3.5 397B A17B measured
LMArena Text: medicine and healthcareNot measured1455Only Qwen3.5 397B A17B measured
LMArena Text: legal and governmentNot measured1441Only Qwen3.5 397B A17B measured
LMArena Text: business and financeNot measured1435Only Qwen3.5 397B A17B measured
Neither model has a result on the other 13 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index07
Web design benchmarks for GPT-5.1-Codex-Mini and Qwen3.5 397B A17B
BenchmarkGPT-5.1-Codex-MiniQwen3.5 397B A17BLeader
Design Arena: websites11111190Qwen3.5 397B A17B
Design Arena: UI components10781160Qwen3.5 397B A17B
Design Arena: game dev10921140Qwen3.5 397B A17B
Design Arena: data viz10971175Qwen3.5 397B A17B
Design Arena: 3D9881160Qwen3.5 397B A17B
Design Arena: all code categories10931179Qwen3.5 397B A17B
Design Arena: SVG9781139Qwen3.5 397B A17B
Design Arena: ASCII art1105Not measuredOnly GPT-5.1-Codex-Mini measured
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 Qwen3.5 397B A17B
BenchmarkGPT-5.1-Codex-MiniQwen3.5 397B A17BLeader
IFBench67.9%78.8%Qwen3.5 397B A17B
Long context reasoning (AA-LCR)66.7%77.3%Qwen3.5 397B A17B
DTBenchNot measured87.5%Only Qwen3.5 397B A17B measured
LMCANot measured37.9%Only Qwen3.5 397B A17B measured
LMArena TextNot measured1437Only Qwen3.5 397B A17B measured
LMArena Text: instruction followingNot measured1424Only Qwen3.5 397B A17B measured
LMArena Text: creative writingNot measured1402Only Qwen3.5 397B A17B measured
LMArena VisionNot measured1262Only Qwen3.5 397B A17B measured
LMArena Text: EnglishNot measured1443Only Qwen3.5 397B A17B measured
LMArena Text: non-EnglishNot measured1430Only Qwen3.5 397B A17B measured
LMArena Text: ChineseNot measured1498Only Qwen3.5 397B A17B measured
LMArena Text: GermanNot measured1445Only Qwen3.5 397B A17B measured
LMArena Text: JapaneseNot measured1429Only Qwen3.5 397B A17B measured
LMArena Text: KoreanNot measured1384Only Qwen3.5 397B A17B measured
LMArena Text: FrenchNot measured1462Only Qwen3.5 397B A17B measured
LMArena Text: SpanishNot measured1441Only Qwen3.5 397B A17B measured
LMArena Text: RussianNot measured1430Only Qwen3.5 397B A17B measured
LMArena Text: PolishNot measured1447Only Qwen3.5 397B A17B measured
LMArena Text: multi-turnNot measured1446Only Qwen3.5 397B A17B measured
LMArena Text: longer queriesNot measured1441Only Qwen3.5 397B A17B measured
LMArena Text: writing and languageNot measured1415Only Qwen3.5 397B A17B measured
LMArena Text: entertainment and mediaNot measured1399Only Qwen3.5 397B A17B measured
LMArena Vision: EnglishNot measured1268Only Qwen3.5 397B A17B measured
LMArena Vision: ChineseNot measured1314Only Qwen3.5 397B A17B measured
LMArena Vision: reading textNot measured1271Only Qwen3.5 397B A17B measured
LMArena Vision: humorNot measured1262Only Qwen3.5 397B A17B measured
LMArena Vision: captioningNot measured1230Only Qwen3.5 397B A17B measured
LMArena Vision: recognizing thingsNot measured1265Only Qwen3.5 397B A17B measured
LMArena Vision: creative writingNot measured1260Only Qwen3.5 397B A17B measured
Neither model has a result on the other 17 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 Qwen3.5 397B A17B
BenchmarkGPT-5.1-Codex-MiniQwen3.5 397B A17BLeader
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
Qwen3.5 397B A17B$0.0016Fits 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
Qwen3.5 397B A17B$0.027Fits 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
Qwen3.5 397B A17B$0.101Fits 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 Qwen3.5 397B A17B
SpecificationOpenAI GPT-5.1-Codex-MiniQwen3.5 397B A17B
MakerOpenAIQwen
WeightsNo public weights listedOpen weights
ReleasedNovember 13, 2025February 16, 2026
Context window400K262K
Input $/Mtok$0.25$0.39
Output $/Mtok$2.00$2.34
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it11
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-5.1-Codex-Mini better than Qwen3.5 397B A17B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-5.1-Codex-Mini for output tokens 1.2x cheaper ($2.00 vs $2.34 per million) and a larger context window (400K against 262K tokens).

Which is cheaper, GPT-5.1-Codex-Mini or Qwen3.5 397B A17B?

GPT-5.1-Codex-Mini costs $0.25 per million input tokens and $2.00 per million output tokens; Qwen3.5 397B A17B costs $0.39 and $2.34. Cost per solved task is known for neither of them.

Which has the bigger context window, GPT-5.1-Codex-Mini or Qwen3.5 397B A17B?

GPT-5.1-Codex-Mini, with 400K tokens against 262K.

How many benchmarks is the GPT-5.1-Codex-Mini vs Qwen3.5 397B A17B comparison based on?

16 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 Qwen3.5 397B A17B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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