Model comparison
o1-pro vs Qwen3.5-9B
Qwen3.5-9B is the stronger model overall, scoring 33.8 to 31.5 on the Noometry Index.
Last verified . 0 shared benchmarks.
Alibaba (Qwen)Summary
- The widest gap is in knowledge, where Qwen3.5-9B leads 46.0 to 29.7.
- Qwen3.5-9B is cheaper at $0.10 / $0.15 per million input/output tokens, against $150 / $600 for o1-pro.
- Qwen3.5-9B accepts more context: 262K tokens versus 200K.
- Qwen3.5-9B has downloadable open weights; the other is API-only.
Side by side
| o1-pro | Qwen3.5-9B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 31.5 | 33.8 |
| Released | 2025-03-19 | 2026-02-23 |
| Weights | Proprietary | Open |
| Context window | 200K | 262K |
| Max output | 100K | 66K |
| Input $ / M tokens | $150 | $0.10 |
| Output $ / M tokens | $600 | $0.15 |
| Results tracked | 3 | 10 |
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Category by category
Coding Not comparable
o1-pro: —, Qwen3.5-9B: 35.9 (#217)
| Benchmark | o1-pro | Qwen3.5-9B |
|---|---|---|
| SciCode | — | 27.5% |
Agentic & Tool Use Not comparable
o1-pro: —, Qwen3.5-9B: 14.5 (#151)
| Benchmark | o1-pro | Qwen3.5-9B |
|---|---|---|
| Terminal-Bench | — | 9.2% |
Reasoning Qwen3.5-9B leads
o1-pro: 20.4 (#239), Qwen3.5-9B: 23.1 (#182)
| Benchmark | o1-pro | Qwen3.5-9B |
|---|---|---|
| ARC-AGI-1 | 23.3% | — |
| CritPt | — | 0.3% |
| Chess Puzzles | — | 12% |
| EnigmaEval | 6.1% | — |
| DTBench | — | 71.2% |
| LMCA | — | 24.5% |
| Epoch Capabilities Index | — | 139.46 |
Math Not comparable
o1-pro: —, Qwen3.5-9B: 34.8 (#192)
| Benchmark | o1-pro | Qwen3.5-9B |
|---|---|---|
| MathArena Final-Answer Competitions | — | 48.5% |
| OTIS Mock AIME 2024-2025 | — | 61.7% |
Knowledge Qwen3.5-9B leads
o1-pro: 29.7 (#234), Qwen3.5-9B: 46.0 (#84)
| Benchmark | o1-pro | Qwen3.5-9B |
|---|---|---|
| GPQA Diamond | — | 79% |
| Humanity's Last Exam | 8.1% | — |
Frequently asked questions
Is o1-pro better than Qwen3.5-9B?
Qwen3.5-9B is the stronger model overall, scoring 33.8 to 31.5 on the Noometry Index.
Which is cheaper, o1-pro or Qwen3.5-9B?
Qwen3.5-9B is cheaper. It lists at $0.10 per million input tokens and $0.15 per million output tokens; o1-pro lists at $150 and $600.
Which has the bigger context window?
Qwen3.5-9B does, with 262K tokens against 200K.
How many benchmarks do o1-pro and Qwen3.5-9B share?
0 benchmarks have published results for both models. o1-pro has 3 scored results on Noometry and Qwen3.5-9B has 10.