Model comparison
o3-pro vs Qwen2-72B
o3-pro is the stronger model overall, scoring 42.9 to 30.0 on the Noometry Index.
Last verified . 2 shared benchmarks.
Alibaba (Qwen)Summary
- They share 2 benchmarks with published results for both. o3-pro scores higher in 5 categories and Qwen2-72B in 0 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in long context, where o3-pro leads 72.2 to 36.1.
- The biggest single-benchmark swing is WeirdML: 58.2% for o3-pro and 11.3% for Qwen2-72B.
- Qwen2-72B has downloadable open weights; the other is API-only.
Side by side
| o3-pro | Qwen2-72B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 42.9 | 30.0 |
| Released | 2025-06-10 | 2024-06-07 |
| Weights | Proprietary | Open |
| Context window | 200K | — |
| Max output | 100K | — |
| Input $ / M tokens | $20 | — |
| Output $ / M tokens | $80 | — |
| Results tracked | 12 | 26 |
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Category by category
Coding o3-pro leads
o3-pro: 55.5 (#24), Qwen2-72B: 29.1 (#310)
| Benchmark | o3-pro | Qwen2-72B |
|---|---|---|
| WeirdML | 58.2% | 11.3% |
| Aider Polyglot | 84.9% | — |
| BigCodeBench Instruct | — | 38.5% |
| LMArena Coding | — | 1196 |
| BigCodeBench Complete | — | 54% |
Agentic & Tool Use Not comparable
o3-pro: —, Qwen2-72B: 17.0 (#146)
| Benchmark | o3-pro | Qwen2-72B |
|---|---|---|
| TheAgentCompany | — | 1.1% |
| METR Time Horizons | — | 29.9% |
Reasoning Too close to call
o3-pro: 23.8 (#171), Qwen2-72B: 23.2 (#181)
| Benchmark | o3-pro | Qwen2-72B |
|---|---|---|
| Epoch Capabilities Index | 147.42 | 125.28 |
| ARC-AGI-2 | 4.9% | — |
| Kagi LLM Benchmark | 72.1% | — |
| ARC-AGI-1 | 59.3% | — |
| LMArena Hard Prompts | — | 1191 |
| DTBench | 86.9% | — |
| LMCA | 38.5% | — |
Math Not comparable
o3-pro: —, Qwen2-72B: 30.2 (#236)
| Benchmark | o3-pro | Qwen2-72B |
|---|---|---|
| LMArena Math | — | 1235 |
| MATH Level 5 | — | 39.1% |
Knowledge o3-pro leads
o3-pro: 29.5 (#238), Qwen2-72B: 21.2 (#275)
| Benchmark | o3-pro | Qwen2-72B |
|---|---|---|
| GPQA Diamond | — | 40.8% |
| Confabulations | 14.2% | — |
| Vectara Hallucination Rate | 23.3% | — |
| LMArena Expert | — | 1171 |
| MMLU | — | 82.4% |
Multilingual Not comparable
o3-pro: —, Qwen2-72B: 35.9 (#244)
| Benchmark | o3-pro | Qwen2-72B |
|---|---|---|
| LMArena Non-English | — | 1176 |
| LMArena Chinese | — | 1240 |
| LMArena French | — | 1170 |
| LMArena German | — | 1151 |
| LMArena Japanese | — | 1111 |
| LMArena Korean | — | 1083 |
| LMArena Russian | — | 1169 |
| LMArena Spanish | — | 1169 |
Instruction Following Not comparable
o3-pro: —, Qwen2-72B: 61.7 (#241)
| Benchmark | o3-pro | Qwen2-72B |
|---|---|---|
| LMArena Instruction Following | — | 1181 |
Long Context o3-pro leads
o3-pro: 72.2 (#1), Qwen2-72B: 36.1 (#235)
| Benchmark | o3-pro | Qwen2-72B |
|---|---|---|
| Fiction.LiveBench | 97.2% | — |
| LMArena Longer Query | — | 1192 |
Writing & Preference o3-pro leads
o3-pro: 57.1 (#133), Qwen2-72B: 40.8 (#241)
| Benchmark | o3-pro | Qwen2-72B |
|---|---|---|
| LMArena Text | — | 1203 |
| LMArena Creative Writing | — | 1181 |
| Short-Story Creative Writing | 84.4% | — |
| LMArena Multi-Turn | — | 1196 |
Frequently asked questions
Is o3-pro better than Qwen2-72B?
o3-pro is the stronger model overall, scoring 42.9 to 30.0 on the Noometry Index.
Is o3-pro or Qwen2-72B better for coding?
o3-pro scores higher on coding benchmarks: 55.5 versus 29.1 in the Noometry coding category.
How many benchmarks do o3-pro and Qwen2-72B share?
2 benchmarks have published results for both models. o3-pro has 12 scored results on Noometry and Qwen2-72B has 26.