Model comparison
o1-pro vs Qwen3-VL 235B-A22B
Qwen3-VL 235B-A22B is the stronger model overall, scoring 43.2 to 31.5 on the Noometry Index.
Last verified . 0 shared benchmarks.
Alibaba (Qwen)Summary
- The widest gap is in knowledge, where Qwen3-VL 235B-A22B leads 40.3 to 29.7.
- Qwen3-VL 235B-A22B 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.
- Qwen3-VL 235B-A22B has downloadable open weights; the other is API-only.
Side by side
| o1-pro | Qwen3-VL 235B-A22B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 31.5 | 43.2 |
| Released | 2025-03-19 | 2025-04 |
| Weights | Proprietary | Open |
| Context window | 200K | 131K |
| Max output | 100K | 33K |
| Input $ / M tokens | $150 | $0.70 |
| Output $ / M tokens | $600 | $2.80 |
| Results tracked | 3 | 18 |
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Category by category
Coding Not comparable
o1-pro: —, Qwen3-VL 235B-A22B: 42.4 (#100)
| Benchmark | o1-pro | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Coding | — | 1439 |
Reasoning Qwen3-VL 235B-A22B leads
o1-pro: 20.4 (#239), Qwen3-VL 235B-A22B: 29.3 (#92)
| Benchmark | o1-pro | Qwen3-VL 235B-A22B |
|---|---|---|
| ARC-AGI-1 | 23.3% | — |
| EnigmaEval | 6.1% | — |
| LMArena Hard Prompts | — | 1428 |
Math Not comparable
o1-pro: —, Qwen3-VL 235B-A22B: 39.0 (#118)
| Benchmark | o1-pro | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Math | — | 1426 |
Knowledge Qwen3-VL 235B-A22B leads
o1-pro: 29.7 (#234), Qwen3-VL 235B-A22B: 40.3 (#121)
| Benchmark | o1-pro | Qwen3-VL 235B-A22B |
|---|---|---|
| Humanity's Last Exam | 8.1% | — |
| LMArena Expert | — | 1442 |
Multimodal Not comparable
o1-pro: —, Qwen3-VL 235B-A22B: 39.8 (#55)
| Benchmark | o1-pro | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Vision | — | 1247 |
Multilingual Not comparable
o1-pro: —, Qwen3-VL 235B-A22B: 51.9 (#97)
| Benchmark | o1-pro | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Non-English | — | 1405 |
| LMArena Chinese | — | 1463 |
| LMArena French | — | 1452 |
| LMArena German | — | 1424 |
| LMArena Japanese | — | 1385 |
| LMArena Korean | — | 1394 |
| LMArena Russian | — | 1408 |
| LMArena Spanish | — | 1428 |
Instruction Following Not comparable
o1-pro: —, Qwen3-VL 235B-A22B: 74.2 (#101)
| Benchmark | o1-pro | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Instruction Following | — | 1406 |
Long Context Not comparable
o1-pro: —, Qwen3-VL 235B-A22B: 43.4 (#98)
| Benchmark | o1-pro | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Longer Query | — | 1420 |
Writing & Preference Not comparable
o1-pro: —, Qwen3-VL 235B-A22B: 60.2 (#99)
| Benchmark | o1-pro | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Text | — | 1420 |
| LMArena Creative Writing | — | 1366 |
| LMArena Multi-Turn | — | 1428 |
Frequently asked questions
Is o1-pro better than Qwen3-VL 235B-A22B?
Qwen3-VL 235B-A22B is the stronger model overall, scoring 43.2 to 31.5 on the Noometry Index.
Which is cheaper, o1-pro or Qwen3-VL 235B-A22B?
Qwen3-VL 235B-A22B 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 Qwen3-VL 235B-A22B share?
0 benchmarks have published results for both models. o1-pro has 3 scored results on Noometry and Qwen3-VL 235B-A22B has 18.