o1 vs Qwen3 Coder 30B A3B Instruct
Updated October 21, 2026. 9 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
o1 and Qwen3 Coder 30B A3B Instruct are level for coding, 61.7 against 60.4 on the Vibe Coding Index, so price and context decide.
Pick Qwen3 Coder 30B A3B Instruct when output tokens cost 214.3x less, or when the context window is larger, 262K against 200K tokens. Pick o1 when what matters is LiveCodeBench (Artificial Analysis run) or AA Intelligence Index, where it leads.
- Shared results
- 9
- o1 only
- 59
- Qwen3 Coder 30B A3B Instruct only
- 7
- Like-for-like categories
- 6 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
No call
Level: 61.7 against 60.4, inside 2 points.
One benchmark behind each score
Intelligence
AA Intelligence Index
o1
o1 leads, 15.2 against 9.6.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only o1 has a GPQA Diamond result, 73.2%.
Directional only
Math
AIME
No call
Only o1 has a AIME result, 71.5%.
Directional only
Knowledge
MMLU Pro
No call
Only o1 has a MMLU Pro result, 83.5%.
Directional only
Web design
Design Arena: websites
No call
Only Qwen3 Coder 30B A3B Instruct has a Design Arena: websites result, 1087.
Directional only
Long documents
Listed context window
Qwen3 Coder 30B A3B Instruct
Qwen3 Coder 30B A3B Instruct takes 262K tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 Coder 30B A3B Instruct
o1 $0.045, Qwen3 Coder 30B A3B Instruct $0.0002 per turn.
List prices
At a glance
- Coding index
- o1 61.7 from 1 benchmark, Qwen3 Coder 30B A3B Instruct 60.4 from 1 benchmark.
- Widest category
- General, 35.0 points apart on average over 2 shared benchmarks.
- Widest single gap
- IFBench: o1 70.3% against Qwen3 Coder 30B A3B Instruct 32.7%, 37.7 points apart on a 0 to 100 scale.
- Output price
- o1 $60.00 against Qwen3 Coder 30B A3B Instruct $0.28 per million output tokens, 214.3x apart.
- Context window
- o1 takes 200K 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 | o1 | Bars | Qwen3 Coder 30B A3B Instruct | Ties |
|---|---|---|---|---|
| Coding | 1 | 1 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| Knowledge | 1 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 8 | 1 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index11
| Benchmark | o1 | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| Aider polyglot | 61.7% | Not measured | Only o1 measured |
| SWE-bench Verified | Not measured | 60.4% | Only Qwen3 Coder 30B A3B Instruct measured |
| SWE-bench Lite | Not measured | 49.7% | Only Qwen3 Coder 30B A3B Instruct measured |
| AA Coding Index | 39.7 | Not measured | Only o1 measured |
| LiveCodeBench (Vals AI) | 50.3% | Not measured | Only o1 measured |
| LiveCodeBench (Artificial Analysis run) | 67.9% | 40.3% | o1 |
| Terminal-Bench Hard (Artificial Analysis run) | 12.9% | 15.2% | Qwen3 Coder 30B A3B Instruct |
| WeirdML | 46.1% | Not measured | Only o1 measured |
| LMArena Text: coding | 1367 | Not measured | Only o1 measured |
| LMArena Text: software and IT | 1366 | Not measured | Only o1 measured |
| Neither model has a result on the other 28 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | o1 | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 15.2 | 9.6 | o1 |
| Epoch Capabilities Index | 141.7 | Not measured | Only o1 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | o1 | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 62.6% | 34.5% | o1 |
| METR time horizons | 51.1% | Not measured | Only o1 measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | o1 | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond | 73.2% | Not measured | Only o1 measured |
| MMMU Pro (Vals AI) | 77.4% | Not measured | Only o1 measured |
| GPQA Diamond (Artificial Analysis run) | 74.7% | 51.6% | o1 |
| Humanity's Last Exam (Artificial Analysis run) | 7.0% | 3.8% | o1 |
| GPQA Diamond (Epoch AI run) | 76.8% | Not measured | Only o1 measured |
| ARC-AGI | 30.7% | Not measured | Only o1 measured |
| SimpleBench | 40.1% | Not measured | Only o1 measured |
| Chess puzzles | 10.0% | Not measured | Only o1 measured |
| VPCT | 37.0% | Not measured | Only o1 measured |
| LMArena Text: hard prompts | 1371 | Not measured | Only o1 measured |
| LMArena Text: expert | 1361 | Not measured | Only o1 measured |
| LMArena Text: hard prompts in English | 1372 | Not measured | Only o1 measured |
| Neither model has a result on the other 9 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | o1 | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| AIME | 71.5% | Not measured | Only o1 measured |
| MATH 500 (Vals AI) | 90.4% | Not measured | Only o1 measured |
| MGSM (Vals AI) | 89.3% | Not measured | Only o1 measured |
| AA Math Index | Not measured | 29.0 | Only Qwen3 Coder 30B A3B Instruct measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 29.0% | Only Qwen3 Coder 30B A3B Instruct measured |
| OTIS Mock AIME | 73.3% | Not measured | Only o1 measured |
| FrontierMath, tiers 1 to 3 | 14.7% | Not measured | Only o1 measured |
| MATH level 5 | 94.7% | Not measured | Only o1 measured |
| LMArena Text: math | 1388 | Not measured | Only o1 measured |
| LMArena Text: mathematical work | 1390 | Not measured | Only o1 measured |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | o1 | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| MMLU Pro | 83.5% | Not measured | Only o1 measured |
| LegalBench (Vals AI) | 80.4% | Not measured | Only o1 measured |
| TaxEval (Vals AI) | 74.3% | Not measured | Only o1 measured |
| MedQA (Vals AI) | 96.5% | Not measured | Only o1 measured |
| MMLU Pro (Artificial Analysis run) | 84.1% | 70.6% | o1 |
| SimpleQA Verified | 41.1% | Not measured | Only o1 measured |
| GeoBench | 80.0% | Not measured | Only o1 measured |
| LMArena Text: science | 1369 | Not measured | Only o1 measured |
| LMArena Text: medicine and healthcare | 1355 | Not measured | Only o1 measured |
| LMArena Text: legal and government | 1368 | Not measured | Only o1 measured |
| LMArena Text: business and finance | 1328 | Not measured | Only o1 measured |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | o1 | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1087 | Only Qwen3 Coder 30B A3B Instruct measured |
| Design Arena: UI components | Not measured | 1046 | Only Qwen3 Coder 30B A3B Instruct measured |
| Design Arena: data viz | Not measured | 1085 | Only Qwen3 Coder 30B A3B Instruct measured |
| Neither model has a result on the other 6 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | o1 | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| IFBench | 70.3% | 32.7% | o1 |
| Long context reasoning (AA-LCR) | 65.0% | 32.7% | o1 |
| DTBench | 74.7% | Not measured | Only o1 measured |
| LMCA | 22.3% | Not measured | Only o1 measured |
| Fiction.LiveBench | 83.3% | Not measured | Only o1 measured |
| Creative writing (Lech Mazur) | 70.2% | Not measured | Only o1 measured |
| LMArena Text | 1366 | Not measured | Only o1 measured |
| LMArena Text: instruction following | 1367 | Not measured | Only o1 measured |
| LMArena Text: creative writing | 1347 | Not measured | Only o1 measured |
| LMArena Vision | 1168 | Not measured | Only o1 measured |
| LMArena Text: English | 1372 | Not measured | Only o1 measured |
| LMArena Text: non-English | 1358 | Not measured | Only o1 measured |
| LMArena Text: Chinese | 1394 | Not measured | Only o1 measured |
| LMArena Text: German | 1337 | Not measured | Only o1 measured |
| LMArena Text: Japanese | 1346 | Not measured | Only o1 measured |
| LMArena Text: Korean | 1396 | Not measured | Only o1 measured |
| LMArena Text: French | 1344 | Not measured | Only o1 measured |
| LMArena Text: Spanish | 1345 | Not measured | Only o1 measured |
| LMArena Text: Russian | 1356 | Not measured | Only o1 measured |
| LMArena Text: multi-turn | 1355 | Not measured | Only o1 measured |
| LMArena Text: longer queries | 1378 | Not measured | Only o1 measured |
| LMArena Text: writing and language | 1360 | Not measured | Only o1 measured |
| LMArena Text: entertainment and media | 1358 | Not measured | Only o1 measured |
| LMArena Vision: English | 1162 | Not measured | Only o1 measured |
| LMArena Vision: Chinese | 1235 | Not measured | Only o1 measured |
| Neither model has a result on the other 21 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | o1 | 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 o1 | Qwen3 Coder 30B A3B Instruct |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | December 17, 2024 | July 31, 2025 |
| Context window | 200K | 262K |
| Input $/Mtok | $15.00 | $0.07 |
| Output $/Mtok | $60.00 | $0.28 |
| Coding index | 61.7 | 60.4 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is o1 better than Qwen3 Coder 30B A3B Instruct for coding?
o1 and Qwen3 Coder 30B A3B Instruct are level for coding, 61.7 against 60.4 on the Vibe Coding Index, so price and context decide. Pick Qwen3 Coder 30B A3B Instruct when output tokens cost 214.3x less, or when the context window is larger, 262K against 200K tokens. Pick o1 when what matters is LiveCodeBench (Artificial Analysis run) or AA Intelligence Index, where it leads.
Which is cheaper, o1 or Qwen3 Coder 30B A3B Instruct?
o1 costs $15.00 per million input tokens and $60.00 per million output tokens; Qwen3 Coder 30B A3B Instruct costs $0.07 and $0.28. Cost per solved task is known for neither of them.
Which has the bigger context window, o1 or Qwen3 Coder 30B A3B Instruct?
Qwen3 Coder 30B A3B Instruct, with 262K tokens against 200K.
How many benchmarks is the o1 vs Qwen3 Coder 30B A3B Instruct comparison based on?
9 benchmarks have a result for both models as of October 21, 2026. o1's coding index rests on 1 independent benchmark 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.