Model comparison
o3 vs Qwen Max
o3 is the stronger model overall, scoring 47.5 to 34.7 on the Noometry Index.
Last verified . 23 shared benchmarks.
Summary
- They share 23 benchmarks with published results for both. o3 scores higher in 8 categories and Qwen Max in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where o3 leads 50.2 to 22.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 84.4% for o3 and 16.1% for Qwen Max.
- Qwen Max is cheaper at $1.60 / $6.40 per million input/output tokens, against $2 / $8 for o3.
- o3 accepts more context: 200K tokens versus 33K.
Side by side
| o3 | Qwen Max | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 47.5 | 34.7 |
| Released | 2025-04-16 | 2024-04-03 |
| Weights | Proprietary | Proprietary |
| Context window | 200K | 33K |
| Max output | 100K | 8K |
| Input $ / M tokens | $2 | $1.60 |
| Output $ / M tokens | $8 | $6.40 |
| Results tracked | 63 | 23 |
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Category by category
Coding o3 leads
o3: 46.8 (#64), Qwen Max: 30.7 (#292)
| Benchmark | o3 | Qwen Max |
|---|---|---|
| Aider Polyglot | 81.3% | 21.8% |
| LMArena Coding | 1408 | 1288 |
| SWE-bench Verified | 62.3% | — |
| SWE-bench Verified (bash only) | 58.4% | — |
| GSO | 8.8% | — |
| WeirdML | 52.4% | — |
| CadEval | 74% | — |
| ALE-Bench | 933.55 | — |
Agentic & Tool Use Not comparable
o3: 34.5 (#44), Qwen Max: —
| Benchmark | o3 | Qwen Max |
|---|---|---|
| Berkeley Function Calling Leaderboard | 63% | — |
| GDPval | 30.8% | — |
| DeepResearch Bench | 45.2% | — |
| OSWorld | 23% | — |
| LMArena Search | 1144 | — |
| METR Time Horizons | 65.4% | — |
Reasoning o3 leads
o3: 32.0 (#78), Qwen Max: 25.1 (#151)
| Benchmark | o3 | Qwen Max |
|---|---|---|
| LMArena Hard Prompts | 1402 | 1269 |
| ARC-AGI-2 | 6.5% | — |
| SimpleBench | 53.1% | — |
| Kagi LLM Benchmark | 67.6% | — |
| ARC-AGI-1 | 60.8% | — |
| CritPt | 1.4% | — |
| Chess Puzzles | 38% | — |
| EnigmaEval | 13.1% | — |
| Mystery Game Puzzles | 29% | — |
| DTBench | 84.8% | — |
| LMCA | 39.7% | — |
| Epoch Capabilities Index | 146.86 | — |
| ForecastBench | 62.5 | — |
Math o3 leads
o3: 50.2 (#58), Qwen Max: 22.3 (#276)
| Benchmark | o3 | Qwen Max |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 84.4% | 16.1% |
| LMArena Math | 1426 | 1275 |
| MATH Level 5 | 97.8% | 67.2% |
| FrontierMath (Feb 2025 set) | 18.7% | 1% |
| FrontierMath (Tiers 1-3) | 33.3% | — |
| Omni-MATH | 71.4% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge o3 leads
o3: 54.6 (#52), Qwen Max: 30.3 (#228)
| Benchmark | o3 | Qwen Max |
|---|---|---|
| GPQA Diamond | 81.8% | 56.1% |
| LMArena Expert | 1402 | 1248 |
| Humanity's Last Exam | 20.3% | — |
| SimpleQA Verified | 49.4% | — |
| MMLU-Pro | 85.9% | — |
| Confabulations | 14.4% | — |
| GPQA (HELM) | 75.3% | — |
Multimodal Not comparable
o3: 41.4 (#36), Qwen Max: —
| Benchmark | o3 | Qwen Max |
|---|---|---|
| LMArena Vision | 1214 | — |
| GeoBench | 74% | — |
| VPCT | 52% | — |
Multilingual o3 leads
o3: 51.7 (#105), Qwen Max: 41.8 (#202)
| Benchmark | o3 | Qwen Max |
|---|---|---|
| LMArena Non-English | 1401 | 1263 |
| LMArena Chinese | 1437 | 1254 |
| LMArena French | 1430 | 1330 |
| LMArena German | 1420 | 1254 |
| LMArena Japanese | 1403 | 1205 |
| LMArena Korean | 1370 | 1142 |
| LMArena Russian | 1406 | 1274 |
| LMArena Spanish | 1395 | 1290 |
Instruction Following o3 leads
o3: 72.8 (#127), Qwen Max: 66.5 (#208)
| Benchmark | o3 | Qwen Max |
|---|---|---|
| LMArena Instruction Following | 1368 | 1262 |
| IFEval | 86.9% | — |
Long Context o3 leads
o3: 53.3 (#6), Qwen Max: 39.4 (#180)
| Benchmark | o3 | Qwen Max |
|---|---|---|
| Fiction.LiveBench | 88.9% | 66.7% |
| LMArena Longer Query | 1372 | 1288 |
| CL-bench | 17.8% | — |
Writing & Preference o3 leads
o3: 63.5 (#64), Qwen Max: 47.8 (#205)
| Benchmark | o3 | Qwen Max |
|---|---|---|
| LMArena Text | 1410 | 1282 |
| LMArena Creative Writing | 1359 | 1248 |
| LMArena Multi-Turn | 1405 | 1277 |
| Short-Story Creative Writing | 83.9% | — |
| EQ-Bench Creative Writing | 1676 | — |
| WildBench | 86.1% | — |
Frequently asked questions
Is o3 better than Qwen Max?
o3 is the stronger model overall, scoring 47.5 to 34.7 on the Noometry Index.
Which is cheaper, o3 or Qwen Max?
Qwen Max is cheaper. It lists at $1.60 per million input tokens and $6.40 per million output tokens; o3 lists at $2 and $8.
Is o3 or Qwen Max better for coding?
o3 scores higher on coding benchmarks: 46.8 versus 30.7 in the Noometry coding category.
Which has the bigger context window?
o3 does, with 200K tokens against 33K.
How many benchmarks do o3 and Qwen Max share?
23 benchmarks have published results for both models. o3 has 63 scored results on Noometry and Qwen Max has 23.