Model comparison
o1-pro vs Qwen2.5 32B Instruct
o1-pro is the stronger model overall, scoring 31.2 to 29.7 on the Noometry Index. Qwen2.5 32B Instruct costs 214× less per token, which makes it the better buy when o1-pro's lead doesn't matter for your workload.
Last verified . 0 shared benchmarks.
Alibaba (Qwen)Summary
- The widest gap is in knowledge, where o1-pro leads 29.3 to 24.9.
- Qwen2.5 32B Instruct is cheaper at $0.70 / $2.80 per million input/output tokens, against $150 / $600 for o1-pro.
- o1-pro accepts more context: 200K tokens versus 131K.
- Qwen2.5 32B Instruct has downloadable open weights; the other is API-only.
Side by side
| o1-pro | Qwen2.5 32B Instruct | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 31.2 | 29.7 |
| Released | 2025-03-19 | 2024-09 |
| Weights | Proprietary | Open |
| Context window | 200K | 131K |
| Max output | 100K | 8K |
| Input $ / M tokens | $150 | $0.70 |
| Output $ / M tokens | $600 | $2.80 |
| Results tracked | 3 | 7 |
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Category by category
Coding Not comparable
o1-pro: —, Qwen2.5 32B Instruct: 38.1 (#165)
| Benchmark | o1-pro | Qwen2.5 32B Instruct |
|---|---|---|
| BigCodeBench Instruct | — | 45% |
| BigCodeBench Complete | — | 52.3% |
Reasoning o1-pro leads
o1-pro: 20.2 (#223), Qwen2.5 32B Instruct: 18.5 (#262)
| Benchmark | o1-pro | Qwen2.5 32B Instruct |
|---|---|---|
| ARC-AGI-1 | 23.3% | — |
| Chess Puzzles | — | 0% |
| EnigmaEval | 6.1% | — |
| Epoch Capabilities Index | — | 128.52 |
Math Not comparable
o1-pro: —, Qwen2.5 32B Instruct: 15.3 (#289)
| Benchmark | o1-pro | Qwen2.5 32B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 7.4% |
| MATH Level 5 | — | 56.1% |
Knowledge o1-pro leads
o1-pro: 29.3 (#227), Qwen2.5 32B Instruct: 24.9 (#259)
| Benchmark | o1-pro | Qwen2.5 32B Instruct |
|---|---|---|
| GPQA Diamond | — | 46.1% |
| Humanity's Last Exam | 8.1% | — |
Frequently asked questions
Is o1-pro better than Qwen2.5 32B Instruct?
o1-pro is the stronger model overall, scoring 31.2 to 29.7 on the Noometry Index. Qwen2.5 32B Instruct costs 214× less per token, which makes it the better buy when o1-pro's lead doesn't matter for your workload.
Which is cheaper, o1-pro or Qwen2.5 32B Instruct?
Qwen2.5 32B Instruct is cheaper. It lists at $0.70 per million input tokens and $2.80 per million output tokens; o1-pro lists at $150 and $600.
Which has the bigger context window?
o1-pro does, with 200K tokens against 131K.
How many benchmarks do o1-pro and Qwen2.5 32B Instruct share?
0 benchmarks have published results for both models. o1-pro has 3 scored results on Noometry and Qwen2.5 32B Instruct has 7.