Model comparison
o3-pro vs Qwen1.5-7B
o3-pro is the stronger model overall, scoring 42.7 to 30.8 on the Noometry Index.
Last verified . 0 shared benchmarks.
Alibaba (Qwen)Summary
- The widest gap is in long context, where o3-pro leads 72.1 to 33.1.
- Qwen1.5-7B has downloadable open weights; the other is API-only.
Side by side
| o3-pro | Qwen1.5-7B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 42.7 | 30.8 |
| Released | 2025-06-10 | 2024-02-04 |
| Weights | Proprietary | Open |
| Context window | 200K | — |
| Max output | 100K | — |
| Input $ / M tokens | $20 | — |
| Output $ / M tokens | $80 | — |
| Results tracked | 12 | 13 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding o3-pro leads
o3-pro: 55.1 (#22), Qwen1.5-7B: 31.6 (#271)
| Benchmark | o3-pro | Qwen1.5-7B |
|---|---|---|
| Aider Polyglot | 84.9% | — |
| WeirdML | 58.2% | — |
| LMArena Coding | — | 1107 |
Reasoning o3-pro leads
o3-pro: 24.1 (#152), Qwen1.5-7B: 19.5 (#237)
| Benchmark | o3-pro | Qwen1.5-7B |
|---|---|---|
| ARC-AGI-2 | 4.9% | — |
| Kagi LLM Benchmark | 72.1% | — |
| ARC-AGI-1 | 59.3% | — |
| LMArena Hard Prompts | — | 1066 |
| DTBench | 86.9% | — |
| LMCA | 38.5% | — |
| Epoch Capabilities Index | 147.43 | — |
Math Not comparable
o3-pro: —, Qwen1.5-7B: 29.0 (#222)
| Benchmark | o3-pro | Qwen1.5-7B |
|---|---|---|
| LMArena Math | — | 1080 |
Knowledge Too close to call
o3-pro: 29.0 (#234), Qwen1.5-7B: 28.2 (#239)
| Benchmark | o3-pro | Qwen1.5-7B |
|---|---|---|
| Confabulations | 14.2% | — |
| Vectara Hallucination Rate | 23.3% | — |
| LMArena Expert | — | 1055 |
| MMLU | — | 62.6% |
Multilingual Not comparable
o3-pro: —, Qwen1.5-7B: 28.6 (#266)
| Benchmark | o3-pro | Qwen1.5-7B |
|---|---|---|
| LMArena Non-English | — | 1058 |
| LMArena Chinese | — | 1140 |
| LMArena Russian | — | 1006 |
Instruction Following Not comparable
o3-pro: —, Qwen1.5-7B: 54.4 (#276)
| Benchmark | o3-pro | Qwen1.5-7B |
|---|---|---|
| LMArena Instruction Following | — | 1058 |
Long Context o3-pro leads
o3-pro: 72.1 (#1), Qwen1.5-7B: 33.1 (#261)
| Benchmark | o3-pro | Qwen1.5-7B |
|---|---|---|
| Fiction.LiveBench | 97.2% | — |
| LMArena Longer Query | — | 1090 |
Writing & Preference o3-pro leads
o3-pro: 57.1 (#128), Qwen1.5-7B: 29.8 (#288)
| Benchmark | o3-pro | Qwen1.5-7B |
|---|---|---|
| LMArena Text | — | 1084 |
| LMArena Creative Writing | — | 1035 |
| Short-Story Creative Writing | 84.4% | — |
| LMArena Multi-Turn | — | 1061 |
Frequently asked questions
Is o3-pro better than Qwen1.5-7B?
o3-pro is the stronger model overall, scoring 42.7 to 30.8 on the Noometry Index.
Is o3-pro or Qwen1.5-7B better for coding?
o3-pro scores higher on coding benchmarks: 55.1 versus 31.6 in the Noometry coding category.
How many benchmarks do o3-pro and Qwen1.5-7B share?
0 benchmarks have published results for both models. o3-pro has 12 scored results on Noometry and Qwen1.5-7B has 13.