GPT-5.1-Codex-Mini vs Qwen3 Coder 480B A35B
GPT-5.1-Codex-Mini leads Qwen3 Coder 480B A35B on the Artificial Analysis Intelligence Index, 20.4 to 11.9, and Qwen3 Coder 480B A35B costs 1.3x less per output token ($1.50 vs $2.00 per million). Updated October 22, 2026; 19 benchmarks have a result for both.
GPT-5.1-Codex-Mini or Qwen3 Coder 480B A35B: 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) and work measured by LMArena WebDev or LMArena WebDev: HTML, where it leads.
- Shared results
- 19
- GPT-5.1-Codex-Mini only
- 3
- Qwen3 Coder 480B A35B only
- 34
- Like-for-like categories
- 8 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.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
GPT-5.1-Codex-Mini
GPT-5.1-Codex-Mini leads, 20.4 against 11.9.
Same board, both measured
Web design
Design Arena: websites
Qwen3 Coder 480B A35B
Qwen3 Coder 480B A35B leads, 1158 against 1111.
Same board, both measured
Long documents
Listed context window
GPT-5.1-Codex-Mini
GPT-5.1-Codex-Mini takes 400K tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 Coder 480B A35B
GPT-5.1-Codex-Mini $0.0013, Qwen3 Coder 480B A35B $0.0010 per turn.
List prices
At a glance
- Coding index
- GPT-5.1-Codex-Mini not benchmarked, Qwen3 Coder 480B A35B not benchmarked.
- Widest category
- Math, 52.4 points apart on average over 2 shared benchmarks.
- Widest single gap
- AA Math Index: GPT-5.1-Codex-Mini 91.7 against Qwen3 Coder 480B A35B 39.3, 52.4 points apart on a 0 to 100 scale.
- Output price
- GPT-5.1-Codex-Mini $2.00 against Qwen3 Coder 480B A35B $1.50 per million output tokens, 1.3x apart.
- Context window
- GPT-5.1-Codex-Mini takes 400K tokens, Qwen3 Coder 480B A35B 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.
| Category | GPT-5.1-Codex-Mini | Bars | Qwen3 Coder 480B A35B | Ties |
|---|---|---|---|---|
| Coding | 3 | 2 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 1 | 0 | ||
| Web design | 1 | 4 | ||
| General | 2 | 0 | ||
| All shared boards | 13 | 6 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index32
| Benchmark | GPT-5.1-Codex-Mini | Qwen3 Coder 480B A35B | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 69.6% | Only Qwen3 Coder 480B A35B measured |
| LMArena WebDev | 1244 | 1275 | Qwen3 Coder 480B A35B |
| LiveCodeBench (Artificial Analysis run) | 83.6% | 58.5% | GPT-5.1-Codex-Mini |
| Terminal-Bench Hard (Artificial Analysis run) | 33.3% | 18.9% | GPT-5.1-Codex-Mini |
| Terminal-Bench | 61.6% | 27.2% | GPT-5.1-Codex-Mini |
| GSO-Bench | Not measured | 4.9% | Only Qwen3 Coder 480B A35B measured |
| WeirdML | Not measured | 41.2% | Only Qwen3 Coder 480B A35B measured |
| ALE-Bench | Not measured | 461.4 | Only Qwen3 Coder 480B A35B measured |
| LMArena Text: coding | Not measured | 1412 | Only Qwen3 Coder 480B A35B measured |
| LMArena Text: software and IT | Not measured | 1393 | Only Qwen3 Coder 480B A35B measured |
| LMArena WebDev: React | Not measured | 1257 | Only Qwen3 Coder 480B A35B measured |
| LMArena WebDev: HTML | 1253 | 1287 | Qwen3 Coder 480B A35B |
| Neither model has a result on the other 27 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.1-Codex-Mini | Qwen3 Coder 480B A35B | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.4 | 11.9 | GPT-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
| Benchmark | GPT-5.1-Codex-Mini | Qwen3 Coder 480B A35B | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 62.9% | 43.6% | GPT-5.1-Codex-Mini |
| Neither model has a result on the other 40 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.1-Codex-Mini | Qwen3 Coder 480B A35B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 81.3% | 61.8% | GPT-5.1-Codex-Mini |
| Humanity's Last Exam (Artificial Analysis run) | 18.5% | 4.5% | GPT-5.1-Codex-Mini |
| LMArena Text: hard prompts | Not measured | 1372 | Only Qwen3 Coder 480B A35B measured |
| LMArena Text: expert | Not measured | 1338 | Only Qwen3 Coder 480B A35B measured |
| LMArena Text: hard prompts in English | Not measured | 1380 | Only Qwen3 Coder 480B A35B measured |
| Kagi LLM Benchmark | Not measured | 49.5% | Only Qwen3 Coder 480B A35B measured |
| Neither model has a result on the other 16 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.1-Codex-Mini | Qwen3 Coder 480B A35B | Leader |
|---|---|---|---|
| AA Math Index | 91.7 | 39.3 | GPT-5.1-Codex-Mini |
| AIME 2025 (Artificial Analysis run) | 91.7% | 39.3% | GPT-5.1-Codex-Mini |
| LMArena Text: math | Not measured | 1365 | Only Qwen3 Coder 480B A35B measured |
| LMArena Text: mathematical work | Not measured | 1367 | Only Qwen3 Coder 480B A35B measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.1-Codex-Mini | Qwen3 Coder 480B A35B | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 82.0% | 78.8% | GPT-5.1-Codex-Mini |
| LMArena Text: science | Not measured | 1347 | Only Qwen3 Coder 480B A35B measured |
| LMArena Text: medicine and healthcare | Not measured | 1347 | Only Qwen3 Coder 480B A35B measured |
| LMArena Text: legal and government | Not measured | 1358 | Only Qwen3 Coder 480B A35B measured |
| LMArena Text: business and finance | Not measured | 1343 | Only Qwen3 Coder 480B A35B measured |
| Neither model has a result on the other 13 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index14
| Benchmark | GPT-5.1-Codex-Mini | Qwen3 Coder 480B A35B | Leader |
|---|---|---|---|
| Design Arena: websites | 1111 | 1158 | Qwen3 Coder 480B A35B |
| Design Arena: UI components | 1078 | 1110 | Qwen3 Coder 480B A35B |
| Design Arena: game dev | 1092 | 1098 | Qwen3 Coder 480B A35B |
| Design Arena: data viz | 1097 | 1084 | GPT-5.1-Codex-Mini |
| Design Arena: 3D | 988 | Not measured | Only GPT-5.1-Codex-Mini measured |
| Design Arena: all code categories | 1093 | 1142 | Qwen3 Coder 480B A35B |
| Design Arena: SVG | 978 | Not measured | Only GPT-5.1-Codex-Mini measured |
| Design Arena: ASCII art | 1105 | Not measured | Only 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
| Benchmark | GPT-5.1-Codex-Mini | Qwen3 Coder 480B A35B | Leader |
|---|---|---|---|
| IFBench | 67.9% | 40.5% | GPT-5.1-Codex-Mini |
| Long context reasoning (AA-LCR) | 66.7% | 45.7% | GPT-5.1-Codex-Mini |
| LMArena Text | Not measured | 1357 | Only Qwen3 Coder 480B A35B measured |
| LMArena Text: instruction following | Not measured | 1355 | Only Qwen3 Coder 480B A35B measured |
| LMArena Text: creative writing | Not measured | 1333 | Only Qwen3 Coder 480B A35B measured |
| LMArena Text: English | Not measured | 1359 | Only Qwen3 Coder 480B A35B measured |
| LMArena Text: non-English | Not measured | 1346 | Only Qwen3 Coder 480B A35B measured |
| LMArena Text: Chinese | Not measured | 1357 | Only Qwen3 Coder 480B A35B measured |
| LMArena Text: German | Not measured | 1325 | Only Qwen3 Coder 480B A35B measured |
| LMArena Text: Japanese | Not measured | 1311 | Only Qwen3 Coder 480B A35B measured |
| LMArena Text: Korean | Not measured | 1305 | Only Qwen3 Coder 480B A35B measured |
| LMArena Text: French | Not measured | 1398 | Only Qwen3 Coder 480B A35B measured |
| LMArena Text: Spanish | Not measured | 1360 | Only Qwen3 Coder 480B A35B measured |
| LMArena Text: Russian | Not measured | 1366 | Only Qwen3 Coder 480B A35B measured |
| LMArena Text: Polish | Not measured | 1344 | Only Qwen3 Coder 480B A35B measured |
| LMArena Text: multi-turn | Not measured | 1366 | Only Qwen3 Coder 480B A35B measured |
| LMArena Text: longer queries | Not measured | 1378 | Only Qwen3 Coder 480B A35B measured |
| LMArena Text: writing and language | Not measured | 1340 | Only Qwen3 Coder 480B A35B measured |
| LMArena Text: entertainment and media | Not measured | 1317 | Only Qwen3 Coder 480B A35B measured |
| Neither model has a result on the other 27 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.1-Codex-Mini | Qwen3 Coder 480B A35B | Leader |
|---|---|---|---|
| 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
Qwen3 Coder 480B A35B costs less
Repository review
50K input + 3K output tokens
GPT-5.1-Codex-Mini costs less
Agent loop
200K input + 10K output tokens
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.
| Specification | OpenAI GPT-5.1-Codex-Mini | Qwen3 Coder 480B A35B |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | November 13, 2025 | July 23, 2025 |
| Context window | 400K | 262K |
| Input $/Mtok | $0.25 | $0.30 |
| Output $/Mtok | $2.00 | $1.50 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.1-Codex-Mini better than Qwen3 Coder 480B A35B 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) and work measured by LMArena WebDev or LMArena WebDev: HTML, where it leads.
Which is cheaper, GPT-5.1-Codex-Mini or Qwen3 Coder 480B A35B?
GPT-5.1-Codex-Mini costs $0.25 per million input tokens and $2.00 per million output tokens; Qwen3 Coder 480B A35B costs $0.30 and $1.50. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-5.1-Codex-Mini or Qwen3 Coder 480B A35B?
GPT-5.1-Codex-Mini, with 400K tokens against 262K.
How many benchmarks is the GPT-5.1-Codex-Mini vs Qwen3 Coder 480B A35B comparison based on?
19 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 Coder 480B A35B's on 1. Where only one model has a result, the page says so instead of naming a winner.