Model comparison
o3-pro vs Qwen1.5-14B
o3-pro is the stronger model overall, scoring 42.9 to 32.7 on the Noometry Index.
Last verified . 0 shared benchmarks.
Alibaba (Qwen)Summary
- The widest gap is in long context, where o3-pro leads 72.2 to 33.7.
- Qwen1.5-14B has downloadable open weights; the other is API-only.
Side by side
| o3-pro | Qwen1.5-14B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 42.9 | 32.7 |
| 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 | 17 |
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Category by category
Coding o3-pro leads
o3-pro: 55.5 (#24), Qwen1.5-14B: 33.1 (#263)
| Benchmark | o3-pro | Qwen1.5-14B |
|---|---|---|
| Aider Polyglot | 84.9% | — |
| WeirdML | 58.2% | — |
| LMArena Coding | — | 1138 |
Reasoning o3-pro leads
o3-pro: 23.8 (#171), Qwen1.5-14B: 21.4 (#223)
| Benchmark | o3-pro | Qwen1.5-14B |
|---|---|---|
| ARC-AGI-2 | 4.9% | — |
| Kagi LLM Benchmark | 72.1% | — |
| ARC-AGI-1 | 59.3% | — |
| LMArena Hard Prompts | — | 1113 |
| DTBench | 86.9% | — |
| LMCA | 38.5% | — |
| Epoch Capabilities Index | 147.42 | — |
Math Not comparable
o3-pro: —, Qwen1.5-14B: 32.4 (#215)
| Benchmark | o3-pro | Qwen1.5-14B |
|---|---|---|
| LMArena Math | — | 1125 |
Knowledge Too close to call
o3-pro: 29.5 (#238), Qwen1.5-14B: 29.8 (#232)
| Benchmark | o3-pro | Qwen1.5-14B |
|---|---|---|
| Confabulations | 14.2% | — |
| Vectara Hallucination Rate | 23.3% | — |
| LMArena Expert | — | 1094 |
| MMLU | — | 68.6% |
Multilingual Not comparable
o3-pro: —, Qwen1.5-14B: 30.7 (#262)
| Benchmark | o3-pro | Qwen1.5-14B |
|---|---|---|
| LMArena Non-English | — | 1095 |
| LMArena Chinese | — | 1147 |
| LMArena French | — | 1116 |
| LMArena German | — | 1043 |
| LMArena Japanese | — | 1019 |
| LMArena Russian | — | 1046 |
| LMArena Spanish | — | 1085 |
Instruction Following Not comparable
o3-pro: —, Qwen1.5-14B: 56.8 (#271)
| Benchmark | o3-pro | Qwen1.5-14B |
|---|---|---|
| LMArena Instruction Following | — | 1102 |
Long Context o3-pro leads
o3-pro: 72.2 (#1), Qwen1.5-14B: 33.7 (#257)
| Benchmark | o3-pro | Qwen1.5-14B |
|---|---|---|
| Fiction.LiveBench | 97.2% | — |
| LMArena Longer Query | — | 1113 |
Writing & Preference o3-pro leads
o3-pro: 57.1 (#133), Qwen1.5-14B: 33.6 (#276)
| Benchmark | o3-pro | Qwen1.5-14B |
|---|---|---|
| LMArena Text | — | 1128 |
| LMArena Creative Writing | — | 1091 |
| Short-Story Creative Writing | 84.4% | — |
| LMArena Multi-Turn | — | 1110 |
Frequently asked questions
Is o3-pro better than Qwen1.5-14B?
o3-pro is the stronger model overall, scoring 42.9 to 32.7 on the Noometry Index.
Is o3-pro or Qwen1.5-14B better for coding?
o3-pro scores higher on coding benchmarks: 55.5 versus 33.1 in the Noometry coding category.
How many benchmarks do o3-pro and Qwen1.5-14B share?
0 benchmarks have published results for both models. o3-pro has 12 scored results on Noometry and Qwen1.5-14B has 17.