GPT-5.1 vs Qwen3 Coder 30B A3B Instruct
Updated October 21, 2026. 15 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Qwen3 Coder 30B A3B Instruct for coding: it scores 60.4 on the Vibe Coding Index against 53.3 for GPT-5.1, though on 1 benchmark against 2.
Pick GPT-5.1 when the context window is larger, 400K against 262K tokens, or when what matters is SWE-bench Verified or LiveCodeBench (Artificial Analysis run), where it leads.
- Shared results
- 15
- GPT-5.1 only
- 85
- Qwen3 Coder 30B A3B Instruct only
- 1
- Like-for-like categories
- 8 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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, four public coding benchmarks
Qwen3 Coder 30B A3B Instruct
Qwen3 Coder 30B A3B Instruct scores 60.4 against 53.3.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.1
GPT-5.1 leads, 24.7 against 9.6.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-5.1 has a GPQA Diamond result, 86.6%.
Directional only
Math
AIME
No call
Only GPT-5.1 has a AIME result, 93.3%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.1 has a MMLU Pro result, 86.4%.
Directional only
Web design
Design Arena: websites
GPT-5.1
GPT-5.1 leads, 1187 against 1087.
Same board, both measured
Long documents
Listed context window
GPT-5.1
GPT-5.1 takes 400K tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 Coder 30B A3B Instruct
GPT-5.1 $0.0063, Qwen3 Coder 30B A3B Instruct $0.0002 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.1 has the number, $1.02.
Directional only
At a glance
- Coding index
- GPT-5.1 53.3 from 2 benchmarks, Qwen3 Coder 30B A3B Instruct 60.4 from 1 benchmark.
- Widest category
- Math, 65.0 points apart on average over 2 shared benchmarks.
- Widest single gap
- AA Math Index: GPT-5.1 94.0 against Qwen3 Coder 30B A3B Instruct 29.0, 65.0 points apart on a 0 to 100 scale.
- Output price
- GPT-5.1 $10.00 against Qwen3 Coder 30B A3B Instruct $0.28 per million output tokens, 35.7x apart.
- Context window
- GPT-5.1 takes 400K tokens, Qwen3 Coder 30B A3B Instruct 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 | Bars | Qwen3 Coder 30B A3B Instruct | Ties |
|---|---|---|---|---|
| Coding | 3 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 1 | 0 | ||
| Web design | 3 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 15 | 0 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index30
| Benchmark | GPT-5.1 | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| SWE-bench Verified | 66.0% | 60.4% | GPT-5.1 |
| SWE-bench Lite | Not measured | 49.7% | Only Qwen3 Coder 30B A3B Instruct measured |
| LMArena WebDev | 1396 | Not measured | Only GPT-5.1 measured |
| AA Coding Index | 49.4 | Not measured | Only GPT-5.1 measured |
| LiveCodeBench (Vals AI) | 86.5% | Not measured | Only GPT-5.1 measured |
| SWE-bench Verified (Vals AI) | 69.8% | Not measured | Only GPT-5.1 measured |
| Vibe Code Bench (Vals AI) | 24.6% | Not measured | Only GPT-5.1 measured |
| LiveCodeBench (Artificial Analysis run) | 86.8% | 40.3% | GPT-5.1 |
| Terminal-Bench Hard (Artificial Analysis run) | 45.5% | 15.2% | GPT-5.1 |
| Terminal-Bench | 47.6% | Not measured | Only GPT-5.1 measured |
| GSO-Bench | 13.7% | Not measured | Only GPT-5.1 measured |
| WeirdML | 60.8% | Not measured | Only GPT-5.1 measured |
| LMArena Text: coding | 1453 | Not measured | Only GPT-5.1 measured |
| LMArena Text: software and IT | 1454 | Not measured | Only GPT-5.1 measured |
| LMArena WebDev: React | 1307 | Not measured | Only GPT-5.1 measured |
| LMArena WebDev: HTML | 1405 | Not measured | Only GPT-5.1 measured |
| LMArena WebDev: from an image | 1421 | Not measured | Only GPT-5.1 measured |
| Neither model has a result on the other 21 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.1 | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 24.7 | 9.6 | GPT-5.1 |
| Epoch Capabilities Index | 149.8 | Not measured | Only GPT-5.1 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.1 | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 81.9% | 34.5% | GPT-5.1 |
| DeepResearch Bench | 42.8% | Not measured | Only GPT-5.1 measured |
| Vending-Bench 2 | $1,473 | Not measured | Only GPT-5.1 measured |
| Neither model has a result on the other 36 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.1 | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond | 86.6% | Not measured | Only GPT-5.1 measured |
| MMMU Pro (Vals AI) | 83.2% | Not measured | Only GPT-5.1 measured |
| GPQA Diamond (Artificial Analysis run) | 87.3% | 51.6% | GPT-5.1 |
| Humanity's Last Exam (Artificial Analysis run) | 28.5% | 3.8% | GPT-5.1 |
| GPQA Diamond (Epoch AI run) | 87.6% | Not measured | Only GPT-5.1 measured |
| ARC-AGI | 72.8% | Not measured | Only GPT-5.1 measured |
| ARC-AGI-2 | 17.6% | Not measured | Only GPT-5.1 measured |
| SimpleBench | 53.2% | Not measured | Only GPT-5.1 measured |
| Chess puzzles | 42.0% | Not measured | Only GPT-5.1 measured |
| Mystery game puzzles | 19.0% | Not measured | Only GPT-5.1 measured |
| VPCT | 58.7% | Not measured | Only GPT-5.1 measured |
| LMArena Text: hard prompts | 1457 | Not measured | Only GPT-5.1 measured |
| LMArena Text: expert | 1470 | Not measured | Only GPT-5.1 measured |
| LMArena Text: hard prompts in English | 1462 | Not measured | Only GPT-5.1 measured |
| LMArena Vision: diagrams | 1264 | Not measured | Only GPT-5.1 measured |
| LMArena Vision: homework | 1272 | Not measured | Only GPT-5.1 measured |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.1 | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| AIME | 93.3% | Not measured | Only GPT-5.1 measured |
| MGSM (Vals AI) | 93.0% | Not measured | Only GPT-5.1 measured |
| AA Math Index | 94.0 | 29.0 | GPT-5.1 |
| AIME 2025 (Artificial Analysis run) | 94.0% | 29.0% | GPT-5.1 |
| OTIS Mock AIME | 88.6% | Not measured | Only GPT-5.1 measured |
| LMArena Text: math | 1446 | Not measured | Only GPT-5.1 measured |
| LMArena Text: mathematical work | 1449 | Not measured | Only GPT-5.1 measured |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.1 | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| MMLU Pro | 86.4% | Not measured | Only GPT-5.1 measured |
| LegalBench (Vals AI) | 85.7% | Not measured | Only GPT-5.1 measured |
| CaseLaw (Vals AI) | 73.4% | Not measured | Only GPT-5.1 measured |
| CorpFin (Vals AI) | 63.8% | Not measured | Only GPT-5.1 measured |
| TaxEval (Vals AI) | 74.9% | Not measured | Only GPT-5.1 measured |
| MortgageTax (Vals AI) | 61.4% | Not measured | Only GPT-5.1 measured |
| MedQA (Vals AI) | 96.4% | Not measured | Only GPT-5.1 measured |
| MedCode (Vals AI) | 52.7% | Not measured | Only GPT-5.1 measured |
| MMLU Pro (Artificial Analysis run) | 87.0% | 70.6% | GPT-5.1 |
| SimpleQA Verified | 48.0% | Not measured | Only GPT-5.1 measured |
| LMArena Text: science | 1459 | Not measured | Only GPT-5.1 measured |
| LMArena Text: medicine and healthcare | 1456 | Not measured | Only GPT-5.1 measured |
| LMArena Text: legal and government | 1459 | Not measured | Only GPT-5.1 measured |
| LMArena Text: business and finance | 1431 | Not measured | Only GPT-5.1 measured |
| Neither model has a result on the other 3 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | GPT-5.1 | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| Design Arena: websites | 1187 | 1087 | GPT-5.1 |
| Design Arena: UI components | 1166 | 1046 | GPT-5.1 |
| Design Arena: game dev | 1179 | Not measured | Only GPT-5.1 measured |
| Design Arena: data viz | 1204 | 1085 | GPT-5.1 |
| Design Arena: 3D | 1061 | Not measured | Only GPT-5.1 measured |
| Design Arena: all code categories | 1171 | Not measured | Only GPT-5.1 measured |
| Design Arena: SVG | 1149 | Not measured | Only GPT-5.1 measured |
| Design Arena: ASCII art | 1118 | Not measured | Only GPT-5.1 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 | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 43.2% | Not measured | Only GPT-5.1 measured |
| MedScribe (Vals AI) | 88.1% | Not measured | Only GPT-5.1 measured |
| IFBench | 72.9% | 32.7% | GPT-5.1 |
| Long context reasoning (AA-LCR) | 80.0% | 32.7% | GPT-5.1 |
| DTBench | 90.1% | Not measured | Only GPT-5.1 measured |
| LMCA | 43.9% | Not measured | Only GPT-5.1 measured |
| CL-bench | 23.7% | Not measured | Only GPT-5.1 measured |
| CL-bench Life | 17.3% | Not measured | Only GPT-5.1 measured |
| LMArena Text | 1443 | Not measured | Only GPT-5.1 measured |
| LMArena Text: instruction following | 1443 | Not measured | Only GPT-5.1 measured |
| LMArena Text: creative writing | 1427 | Not measured | Only GPT-5.1 measured |
| LMArena Vision | 1250 | Not measured | Only GPT-5.1 measured |
| LMArena Text: English | 1451 | Not measured | Only GPT-5.1 measured |
| LMArena Text: non-English | 1431 | Not measured | Only GPT-5.1 measured |
| LMArena Text: Chinese | 1495 | Not measured | Only GPT-5.1 measured |
| LMArena Text: German | 1438 | Not measured | Only GPT-5.1 measured |
| LMArena Text: Japanese | 1453 | Not measured | Only GPT-5.1 measured |
| LMArena Text: Korean | 1401 | Not measured | Only GPT-5.1 measured |
| LMArena Text: French | 1450 | Not measured | Only GPT-5.1 measured |
| LMArena Text: Spanish | 1433 | Not measured | Only GPT-5.1 measured |
| LMArena Text: Russian | 1435 | Not measured | Only GPT-5.1 measured |
| LMArena Text: Polish | 1440 | Not measured | Only GPT-5.1 measured |
| LMArena Text: multi-turn | 1450 | Not measured | Only GPT-5.1 measured |
| LMArena Text: longer queries | 1448 | Not measured | Only GPT-5.1 measured |
| LMArena Text: writing and language | 1428 | Not measured | Only GPT-5.1 measured |
| LMArena Text: entertainment and media | 1415 | Not measured | Only GPT-5.1 measured |
| LMArena Vision: English | 1252 | Not measured | Only GPT-5.1 measured |
| LMArena Vision: Chinese | 1270 | Not measured | Only GPT-5.1 measured |
| LMArena Vision: reading text | 1255 | Not measured | Only GPT-5.1 measured |
| LMArena Vision: humor | 1263 | Not measured | Only GPT-5.1 measured |
| LMArena Vision: captioning | 1252 | Not measured | Only GPT-5.1 measured |
| LMArena Vision: recognizing things | 1232 | Not measured | Only GPT-5.1 measured |
| LMArena Vision: creative writing | 1266 | Not measured | Only GPT-5.1 measured |
| LMArena Document | 1403 | Not measured | Only GPT-5.1 measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.1 | Qwen3 Coder 30B A3B Instruct | 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 30B A3B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen3 Coder 30B A3B Instruct costs less
Agent loop
200K input + 10K output tokens
Qwen3 Coder 30B A3B Instruct 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 | Qwen3 Coder 30B A3B Instruct |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | November 13, 2025 | July 31, 2025 |
| Context window | 400K | 262K |
| Input $/Mtok | $1.25 | $0.07 |
| Output $/Mtok | $10.00 | $0.28 |
| Coding index | 53.3 | 60.4 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $1.02 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.1 better than Qwen3 Coder 30B A3B Instruct for coding?
Pick Qwen3 Coder 30B A3B Instruct for coding: it scores 60.4 on the Vibe Coding Index against 53.3 for GPT-5.1, though on 1 benchmark against 2. Pick GPT-5.1 when the context window is larger, 400K against 262K tokens, or when what matters is SWE-bench Verified or LiveCodeBench (Artificial Analysis run), where it leads.
Which is cheaper, GPT-5.1 or Qwen3 Coder 30B A3B Instruct?
GPT-5.1 costs $1.25 per million input tokens and $10.00 per million output tokens; Qwen3 Coder 30B A3B Instruct costs $0.07 and $0.28. Cost per solved task is known for GPT-5.1 only.
Which has the bigger context window, GPT-5.1 or Qwen3 Coder 30B A3B Instruct?
GPT-5.1, with 400K tokens against 262K.
How many benchmarks is the GPT-5.1 vs Qwen3 Coder 30B A3B Instruct comparison based on?
15 benchmarks have a result for both models as of October 21, 2026. GPT-5.1's coding index rests on 2 independent benchmarks and Qwen3 Coder 30B A3B Instruct's on 1. Where only one model has a result, the page says so instead of naming a winner.