o1 vs Qwen3 Next 80B A3B Instruct
o1 leads Qwen3 Next 80B A3B Instruct on the Artificial Analysis Intelligence Index, 15.2 to 9.6, and Qwen3 Next 80B A3B Instruct costs 54.5x less per output token ($1.10 vs $60.00 per million). Updated October 21, 2026; 37 benchmarks have a result for both.
o1 or Qwen3 Next 80B A3B Instruct: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick o1 for work measured by LiveCodeBench (Artificial Analysis run) or LMArena Text: coding, where it leads.
- Shared results
- 37
- o1 only
- 31
- Qwen3 Next 80B A3B Instruct only
- 3
- 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.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
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
Long documents
Listed context window
Qwen3 Next 80B A3B Instruct
Qwen3 Next 80B A3B Instruct takes 262K tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 Next 80B A3B Instruct
o1 $0.045, Qwen3 Next 80B A3B Instruct $0.0006 per turn.
List prices
At a glance
- Coding index
- o1 not benchmarked, Qwen3 Next 80B A3B Instruct not benchmarked.
- Widest category
- Agentic work, 21.1 points apart on average over 1 shared benchmark.
- Widest single gap
- Fiction.LiveBench: o1 83.3% against Qwen3 Next 80B A3B Instruct 55.6%, 27.7 points apart on a 0 to 100 scale.
- Output price
- o1 $60.00 against Qwen3 Next 80B A3B Instruct $1.10 per million output tokens, 54.5x apart.
- Context window
- o1 takes 200K tokens, Qwen3 Next 80B 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 Next 80B A3B Instruct | Ties |
|---|---|---|---|---|
| Coding | 1 | 3 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 0 | 5 | ||
| Math | 0 | 2 | ||
| Knowledge | 1 | 4 | ||
| General | 7 | 12 | ||
| All shared boards | 11 | 26 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index13
| Benchmark | o1 | Qwen3 Next 80B A3B Instruct | Leader |
|---|---|---|---|
| Aider polyglot | 61.7% | Not measured | Only o1 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% | 78.4% | Qwen3 Next 80B A3B Instruct |
| Terminal-Bench Hard (Artificial Analysis run) | 12.9% | 9.8% | o1 |
| WeirdML | 46.1% | Not measured | Only o1 measured |
| LMArena Text: coding | 1367 | 1440 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: software and IT | 1366 | 1447 | Qwen3 Next 80B A3B Instruct |
| Neither model has a result on the other 30 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | o1 | Qwen3 Next 80B 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 Next 80B A3B Instruct | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 62.6% | 41.5% | 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 index05
| Benchmark | o1 | Qwen3 Next 80B 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% | 75.9% | Qwen3 Next 80B A3B Instruct |
| Humanity's Last Exam (Artificial Analysis run) | 7.0% | 12.6% | Qwen3 Next 80B A3B Instruct |
| 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 | 1428 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: expert | 1361 | 1417 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: hard prompts in English | 1372 | 1431 | Qwen3 Next 80B A3B Instruct |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | o1 | Qwen3 Next 80B 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 | 84.3 | Only Qwen3 Next 80B A3B Instruct measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 84.3% | Only Qwen3 Next 80B 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 | 1440 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: mathematical work | 1390 | 1434 | Qwen3 Next 80B A3B Instruct |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index14
| Benchmark | o1 | Qwen3 Next 80B 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% | 82.4% | o1 |
| SimpleQA Verified | 41.1% | Not measured | Only o1 measured |
| GeoBench | 80.0% | Not measured | Only o1 measured |
| LMArena Text: science | 1369 | 1434 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: medicine and healthcare | 1355 | 1455 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: legal and government | 1368 | 1431 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: business and finance | 1328 | 1422 | Qwen3 Next 80B A3B Instruct |
| Neither model has a result on the other 6 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | o1 | Qwen3 Next 80B A3B Instruct | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index712
| Benchmark | o1 | Qwen3 Next 80B A3B Instruct | Leader |
|---|---|---|---|
| IFBench | 70.3% | 60.7% | o1 |
| Long context reasoning (AA-LCR) | 65.0% | 63.7% | o1 |
| DTBench | 74.7% | Not measured | Only o1 measured |
| LMCA | 22.3% | Not measured | Only o1 measured |
| Fiction.LiveBench | 83.3% | 55.6% | o1 |
| Creative writing (Lech Mazur) | 70.2% | Not measured | Only o1 measured |
| LMArena Text | 1366 | 1417 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: instruction following | 1367 | 1388 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: creative writing | 1347 | 1333 | o1 |
| LMArena Vision | 1168 | Not measured | Only o1 measured |
| LMArena Text: English | 1372 | 1421 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: non-English | 1358 | 1407 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: Chinese | 1394 | 1460 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: German | 1337 | 1416 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: Japanese | 1346 | 1395 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: Korean | 1396 | 1363 | o1 |
| LMArena Text: French | 1344 | 1414 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: Spanish | 1345 | 1435 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: Russian | 1356 | 1404 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: Polish | Not measured | 1398 | Only Qwen3 Next 80B A3B Instruct measured |
| LMArena Text: multi-turn | 1355 | 1416 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: longer queries | 1378 | 1402 | Qwen3 Next 80B A3B Instruct |
| LMArena Text: writing and language | 1360 | 1355 | o1 |
| LMArena Text: entertainment and media | 1358 | 1349 | o1 |
| 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 20 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | o1 | Qwen3 Next 80B 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 Next 80B A3B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen3 Next 80B A3B Instruct costs less
Agent loop
200K input + 10K output tokens
Qwen3 Next 80B 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 Next 80B A3B Instruct |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | December 17, 2024 | September 11, 2025 |
| Context window | 200K | 262K |
| Input $/Mtok | $15.00 | $0.10 |
| Output $/Mtok | $60.00 | $1.10 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is o1 better than Qwen3 Next 80B A3B Instruct for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick o1 for work measured by LiveCodeBench (Artificial Analysis run) or LMArena Text: coding, where it leads.
Which is cheaper, o1 or Qwen3 Next 80B A3B Instruct?
o1 costs $15.00 per million input tokens and $60.00 per million output tokens; Qwen3 Next 80B A3B Instruct costs $0.10 and $1.10. Cost per solved task is known for neither of them.
Which has the bigger context window, o1 or Qwen3 Next 80B A3B Instruct?
Qwen3 Next 80B A3B Instruct, with 262K tokens against 200K.
How many benchmarks is the o1 vs Qwen3 Next 80B A3B Instruct comparison based on?
37 benchmarks have a result for both models as of October 21, 2026. o1's coding index rests on 0 independent benchmarks and Qwen3 Next 80B A3B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.