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GPT-5.1-Codex-Mini vs Qwen3 30B A3B Instruct 2507

GPT-5.1-Codex-Mini leads Qwen3 30B A3B Instruct 2507 on the Artificial Analysis Intelligence Index, 20.4 to 7.5, and Qwen3 30B A3B Instruct 2507 costs 6.7x less per output token ($0.30 vs $2.00 per million). Updated October 22, 2026; 11 benchmarks have a result for both.

Replace GPT-5.1-Codex-Mini Replace Qwen3 30B A3B Instruct 2507
GPT-5.1-Codex-MiniOpenAI
Coding
No data
Overall
No data
Output $/M
$2.00
11
Qwen3 30B A3B Instruct 2507Qwen
Coding
No data
Overall
41.5
Output $/M
$0.30
0
vs boards won of 11 shared

GPT-5.1-Codex-Mini or Qwen3 30B A3B Instruct 2507: 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 a larger context window (400K against 262K tokens).

Model AGPT-5.1-Codex-MiniOpenAINot benchmarked1 independent benchmarkNo cost per solved taskModel BQwen3 30B A3B Instruct 2507QwenNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
11
GPT-5.1-Codex-Mini only
11
Qwen3 30B A3B Instruct 2507 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-5.1-Codex-Mini not benchmarked, Qwen3 30B A3B Instruct 2507 not benchmarked.
Widest category
Agentic work, 34.8 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GPT-5.1-Codex-Mini 62.9% against Qwen3 30B A3B Instruct 2507 28.1%, 34.8 points apart on a 0 to 100 scale.
Output price
GPT-5.1-Codex-Mini $2.00 against Qwen3 30B A3B Instruct 2507 $0.30 per million output tokens, 6.7x apart.
Context window
GPT-5.1-Codex-Mini takes 400K tokens, Qwen3 30B A3B Instruct 2507 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 30B A3B Instruct 2507Ties
Coding20
Intelligence10
Agentic work10
Reasoning20
Math20
Knowledge10
General20
All shared boards110
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
Coding benchmarks for GPT-5.1-Codex-Mini and Qwen3 30B A3B Instruct 2507
BenchmarkGPT-5.1-Codex-MiniQwen3 30B A3B Instruct 2507Leader
LMArena WebDev1244Not measuredOnly GPT-5.1-Codex-Mini measured
LiveCodeBench (Artificial Analysis run)83.6%70.7%GPT-5.1-Codex-Mini
SciCodeNot measured33.0%Only Qwen3 30B A3B Instruct 2507 measured
Terminal-Bench Hard (Artificial Analysis run)33.3%6.1%GPT-5.1-Codex-Mini
Terminal-Bench61.6%Not measuredOnly GPT-5.1-Codex-Mini measured
LMArena Text: codingNot measured1416Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: software and ITNot measured1417Only Qwen3 30B A3B Instruct 2507 measured
LMArena WebDev: HTML1253Not measuredOnly GPT-5.1-Codex-Mini measured
Neither model has a result on the other 31 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GPT-5.1-Codex-Mini and Qwen3 30B A3B Instruct 2507
BenchmarkGPT-5.1-Codex-MiniQwen3 30B A3B Instruct 2507Leader
AA Intelligence Index20.47.5GPT-5.1-Codex-Mini
Neither model has a result on the other 1 board here
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GPT-5.1-Codex-Mini and Qwen3 30B A3B Instruct 2507
BenchmarkGPT-5.1-Codex-MiniQwen3 30B A3B Instruct 2507Leader
τ²-Bench Telecom62.9%28.1%GPT-5.1-Codex-Mini
Berkeley Function Calling Leaderboard (BFCL)Not measured41.4%Only Qwen3 30B A3B Instruct 2507 measured
Neither model has a result on the other 39 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
Reasoning benchmarks for GPT-5.1-Codex-Mini and Qwen3 30B A3B Instruct 2507
BenchmarkGPT-5.1-Codex-MiniQwen3 30B A3B Instruct 2507Leader
GPQA Diamond (Artificial Analysis run)81.3%70.7%GPT-5.1-Codex-Mini
Humanity's Last Exam (Artificial Analysis run)18.5%10.3%GPT-5.1-Codex-Mini
GPQA Diamond (Epoch AI run)Not measured55.6%Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: hard promptsNot measured1398Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: expertNot measured1397Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: hard prompts in EnglishNot measured1406Only Qwen3 30B A3B Instruct 2507 measured
Neither model has a result on the other 16 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for GPT-5.1-Codex-Mini and Qwen3 30B A3B Instruct 2507
BenchmarkGPT-5.1-Codex-MiniQwen3 30B A3B Instruct 2507Leader
AA Math Index91.766.3GPT-5.1-Codex-Mini
AIME 2025 (Artificial Analysis run)91.7%66.3%GPT-5.1-Codex-Mini
OTIS Mock AIMENot measured62.2%Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: mathNot measured1394Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: mathematical workNot measured1411Only Qwen3 30B A3B Instruct 2507 measured
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
Knowledge benchmarks for GPT-5.1-Codex-Mini and Qwen3 30B A3B Instruct 2507
BenchmarkGPT-5.1-Codex-MiniQwen3 30B A3B Instruct 2507Leader
MMLU Pro (Artificial Analysis run)82.0%80.5%GPT-5.1-Codex-Mini
LMArena Text: scienceNot measured1393Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: medicine and healthcareNot measured1392Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: legal and governmentNot measured1387Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: business and financeNot measured1389Only Qwen3 30B A3B Instruct 2507 measured
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-5.1-Codex-Mini and Qwen3 30B A3B Instruct 2507
BenchmarkGPT-5.1-Codex-MiniQwen3 30B A3B Instruct 2507Leader
Design Arena: websites1111Not measuredOnly GPT-5.1-Codex-Mini measured
Design Arena: UI components1078Not measuredOnly GPT-5.1-Codex-Mini measured
Design Arena: game dev1092Not measuredOnly GPT-5.1-Codex-Mini measured
Design Arena: data viz1097Not measuredOnly GPT-5.1-Codex-Mini measured
Design Arena: 3D988Not measuredOnly GPT-5.1-Codex-Mini measured
Design Arena: all code categories1093Not measuredOnly GPT-5.1-Codex-Mini measured
Design Arena: SVG978Not measuredOnly GPT-5.1-Codex-Mini measured
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 index20
General benchmarks for GPT-5.1-Codex-Mini and Qwen3 30B A3B Instruct 2507
BenchmarkGPT-5.1-Codex-MiniQwen3 30B A3B Instruct 2507Leader
IFBench67.9%50.7%GPT-5.1-Codex-Mini
Long context reasoning (AA-LCR)66.7%61.3%GPT-5.1-Codex-Mini
DTBenchNot measured67.2%Only Qwen3 30B A3B Instruct 2507 measured
LMCANot measured22.4%Only Qwen3 30B A3B Instruct 2507 measured
LMArena TextNot measured1384Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: instruction followingNot measured1363Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: creative writingNot measured1317Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: EnglishNot measured1391Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: non-EnglishNot measured1372Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: ChineseNot measured1432Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: GermanNot measured1379Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: JapaneseNot measured1337Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: KoreanNot measured1330Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: FrenchNot measured1419Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: SpanishNot measured1404Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: RussianNot measured1369Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: PolishNot measured1353Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: multi-turnNot measured1378Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: longer queriesNot measured1378Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: writing and languageNot measured1336Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: entertainment and mediaNot measured1334Only Qwen3 30B A3B Instruct 2507 measured
Neither model has a result on the other 25 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 30B A3B Instruct 2507
BenchmarkGPT-5.1-Codex-MiniQwen3 30B A3B Instruct 2507Leader
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 30B A3B Instruct 2507$0.0002Fits in one request

Qwen3 30B A3B Instruct 2507 costs less

Repository review

50K input + 3K output tokens

GPT-5.1-Codex-Mini$0.018Fits in one request
Qwen3 30B A3B Instruct 2507$0.0054Fits in one request

Qwen3 30B A3B Instruct 2507 costs less

Agent loop

200K input + 10K output tokens

GPT-5.1-Codex-Mini$0.070Fits in one request
Qwen3 30B A3B Instruct 2507$0.021Fits in one request

Qwen3 30B A3B Instruct 2507 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 30B A3B Instruct 2507
SpecificationOpenAI GPT-5.1-Codex-MiniQwen3 30B A3B Instruct 2507
MakerOpenAIQwen
WeightsNo public weights listedOpen weights
ReleasedNovember 13, 2025July 29, 2025
Context window400K262K
Input $/Mtok$0.25$0.09
Output $/Mtok$2.00$0.30
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it10
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-5.1-Codex-Mini better than Qwen3 30B A3B Instruct 2507 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-5.1-Codex-Mini for a larger context window (400K against 262K tokens).

Which is cheaper, GPT-5.1-Codex-Mini or Qwen3 30B A3B Instruct 2507?

GPT-5.1-Codex-Mini costs $0.25 per million input tokens and $2.00 per million output tokens; Qwen3 30B A3B Instruct 2507 costs $0.09 and $0.30. Cost per solved task is known for neither of them.

Which has the bigger context window, GPT-5.1-Codex-Mini or Qwen3 30B A3B Instruct 2507?

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

How many benchmarks is the GPT-5.1-Codex-Mini vs Qwen3 30B A3B Instruct 2507 comparison based on?

11 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 30B A3B Instruct 2507's on 0. Where only one model has a result, the page says so instead of naming a winner.

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