Model comparison
o3-mini vs Qwen3-Next 80B-A3B Instruct
Qwen3-Next 80B-A3B Instruct is the stronger model overall, scoring 43.0 to 36.7 on the Noometry Index.
Last verified . 18 shared benchmarks.
Alibaba (Qwen)Summary
- They share 18 benchmarks with published results for both. o3-mini scores higher in 1 category and Qwen3-Next 80B-A3B Instruct in 7 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Qwen3-Next 80B-A3B Instruct leads 31.1 to 16.3.
- The biggest single-benchmark swing is Fiction.LiveBench: 50% for o3-mini and 55.6% for Qwen3-Next 80B-A3B Instruct.
- Qwen3-Next 80B-A3B Instruct is cheaper at $0.50 / $2 per million input/output tokens, against $1.10 / $4.40 for o3-mini.
- o3-mini accepts more context: 200K tokens versus 131K.
- Qwen3-Next 80B-A3B Instruct has downloadable open weights; the other is API-only.
Side by side
| o3-mini | Qwen3-Next 80B-A3B Instruct | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 36.7 | 43.0 |
| Released | 2024-12-20 | 2025-09 |
| Weights | Proprietary | Open |
| Context window | 200K | 131K |
| Max output | 100K | 33K |
| Input $ / M tokens | $1.10 | $0.50 |
| Output $ / M tokens | $4.40 | $2 |
| Results tracked | 51 | 25 |
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Category by category
Coding Qwen3-Next 80B-A3B Instruct leads
o3-mini: 40.8 (#132), Qwen3-Next 80B-A3B Instruct: 42.5 (#98)
| Benchmark | o3-mini | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Coding | 1378 | 1440 |
| Aider Polyglot | 60.4% | — |
| SciCode | 39.8% | — |
| GSO | 1.3% | — |
| WeirdML | 43.7% | — |
| LiveBench Coding | 82.7% | — |
| CadEval | 54% | — |
Agentic & Tool Use Not comparable
o3-mini: 29.6 (#84), Qwen3-Next 80B-A3B Instruct: —
| Benchmark | o3-mini | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Cybench | 22.5% | — |
Reasoning Qwen3-Next 80B-A3B Instruct leads
o3-mini: 16.3 (#305), Qwen3-Next 80B-A3B Instruct: 31.1 (#81)
| Benchmark | o3-mini | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Hard Prompts | 1366 | 1428 |
| ARC-AGI-2 | 3% | — |
| SimpleBench | 22.8% | — |
| Kagi LLM Benchmark | — | 66.7% |
| ARC-AGI-1 | 34.5% | — |
| CritPt | 0.3% | — |
| Chess Puzzles | 17% | — |
| LiveBench Reasoning | 89.6% | — |
| Mystery Game Puzzles | 7% | — |
| DTBench | 68.8% | — |
| LiveBench Data Analysis | 70.6% | — |
| LMCA | 19% | — |
| Epoch Capabilities Index | 140.34 | — |
| ForecastBench | 59.6 | — |
| LiveBench | 75.9% | — |
Math Qwen3-Next 80B-A3B Instruct leads
o3-mini: 28.1 (#244), Qwen3-Next 80B-A3B Instruct: 38.8 (#126)
| Benchmark | o3-mini | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Math | 1396 | 1440 |
| FrontierMath (Tiers 1-3) | 18.6% | — |
| FrontierMath Tier 4 | 0% | — |
| OTIS Mock AIME 2024-2025 | 76.9% | — |
| Omni-MATH | — | 46.7% |
| LiveBench Math | 77.3% | — |
| MATH Level 5 | 96.5% | — |
| FrontierMath (Feb 2025 set) | 12.4% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge Qwen3-Next 80B-A3B Instruct leads
o3-mini: 38.3 (#146), Qwen3-Next 80B-A3B Instruct: 41.8 (#106)
| Benchmark | o3-mini | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Expert | 1364 | 1417 |
| GPQA Diamond | 77% | — |
| SimpleQA Verified | 15.3% | — |
| MMLU-Pro | — | 78.6% |
| Confabulations | 17.9% | — |
| Vectara Hallucination Rate | — | 9.3% |
| GPQA (HELM) | — | 63% |
Multilingual Qwen3-Next 80B-A3B Instruct leads
o3-mini: 45.7 (#164), Qwen3-Next 80B-A3B Instruct: 52.1 (#93)
| Benchmark | o3-mini | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Non-English | 1319 | 1407 |
| LMArena Chinese | 1379 | 1460 |
| LMArena French | 1334 | 1413 |
| LMArena German | 1303 | 1417 |
| LMArena Japanese | 1286 | 1395 |
| LMArena Korean | 1314 | 1364 |
| LMArena Russian | 1304 | 1404 |
| LMArena Spanish | 1321 | 1435 |
Instruction Following o3-mini leads
o3-mini: 75.1 (#72), Qwen3-Next 80B-A3B Instruct: 70.8 (#159)
| Benchmark | o3-mini | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Instruction Following | 1337 | 1389 |
| LiveBench Instruction Following | 84.4% | — |
| IFEval | — | 81% |
Long Context Qwen3-Next 80B-A3B Instruct leads
o3-mini: 33.8 (#256), Qwen3-Next 80B-A3B Instruct: 37.0 (#223)
| Benchmark | o3-mini | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Fiction.LiveBench | 50% | 55.6% |
| LMArena Longer Query | 1343 | 1403 |
Writing & Preference Qwen3-Next 80B-A3B Instruct leads
o3-mini: 50.3 (#182), Qwen3-Next 80B-A3B Instruct: 58.0 (#121)
| Benchmark | o3-mini | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Text | 1337 | 1417 |
| LMArena Creative Writing | 1286 | 1334 |
| LMArena Multi-Turn | 1320 | 1416 |
| Short-Story Creative Writing | 61.7% | — |
| WildBench | — | 80.7% |
| LiveBench Language | 50.7% | — |
Frequently asked questions
Is o3-mini better than Qwen3-Next 80B-A3B Instruct?
Qwen3-Next 80B-A3B Instruct is the stronger model overall, scoring 43.0 to 36.7 on the Noometry Index.
Which is cheaper, o3-mini or Qwen3-Next 80B-A3B Instruct?
Qwen3-Next 80B-A3B Instruct is cheaper. It lists at $0.50 per million input tokens and $2 per million output tokens; o3-mini lists at $1.10 and $4.40.
Is o3-mini or Qwen3-Next 80B-A3B Instruct better for coding?
Qwen3-Next 80B-A3B Instruct scores higher on coding benchmarks: 42.5 versus 40.8 in the Noometry coding category.
Which has the bigger context window?
o3-mini does, with 200K tokens against 131K.
How many benchmarks do o3-mini and Qwen3-Next 80B-A3B Instruct share?
18 benchmarks have published results for both models. o3-mini has 51 scored results on Noometry and Qwen3-Next 80B-A3B Instruct has 25.