Model comparison
o1-pro vs Qwen3 14B
Qwen3 14B is the stronger model overall, scoring 35.5 to 31.5 on the Noometry Index.
Last verified . 0 shared benchmarks.
Alibaba (Qwen)Summary
- The widest gap is in knowledge, where Qwen3 14B leads 39.3 to 29.7.
- Qwen3 14B is cheaper at $0.35 / $1.40 per million input/output tokens, against $150 / $600 for o1-pro.
- o1-pro accepts more context: 200K tokens versus 131K.
- Qwen3 14B has downloadable open weights; the other is API-only.
Side by side
| o1-pro | Qwen3 14B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 31.5 | 35.5 |
| Released | 2025-03-19 | 2025-04 |
| Weights | Proprietary | Open |
| Context window | 200K | 131K |
| Max output | 100K | 8K |
| Input $ / M tokens | $150 | $0.35 |
| Output $ / M tokens | $600 | $1.40 |
| Results tracked | 3 | 12 |
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Category by category
Coding Not comparable
o1-pro: —, Qwen3 14B: 37.3 (#195)
| Benchmark | o1-pro | Qwen3 14B |
|---|---|---|
| SciCode | — | 31.6% |
Agentic & Tool Use Not comparable
o1-pro: —, Qwen3 14B: 29.6 (#83)
| Benchmark | o1-pro | Qwen3 14B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 41% |
Reasoning o1-pro leads
o1-pro: 20.4 (#239), Qwen3 14B: 18.5 (#280)
| Benchmark | o1-pro | Qwen3 14B |
|---|---|---|
| Kagi LLM Benchmark | — | 49.1% |
| ARC-AGI-1 | 23.3% | — |
| CritPt | — | 0% |
| Chess Puzzles | — | 4% |
| EnigmaEval | 6.1% | — |
| DTBench | — | 64% |
| LMCA | — | 18.2% |
| Epoch Capabilities Index | — | 138.23 |
Math Not comparable
o1-pro: —, Qwen3 14B: 38.6 (#133)
| Benchmark | o1-pro | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 66.4% |
Knowledge Qwen3 14B leads
o1-pro: 29.7 (#234), Qwen3 14B: 39.3 (#134)
| Benchmark | o1-pro | Qwen3 14B |
|---|---|---|
| GPQA Diamond | — | 63.8% |
| Humanity's Last Exam | 8.1% | — |
| Vectara Hallucination Rate | — | 5.4% |
Long Context Not comparable
o1-pro: —, Qwen3 14B: 38.1 (#204)
| Benchmark | o1-pro | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | — | 62.5% |
Frequently asked questions
Is o1-pro better than Qwen3 14B?
Qwen3 14B is the stronger model overall, scoring 35.5 to 31.5 on the Noometry Index.
Which is cheaper, o1-pro or Qwen3 14B?
Qwen3 14B is cheaper. It lists at $0.35 per million input tokens and $1.40 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 14B share?
0 benchmarks have published results for both models. o1-pro has 3 scored results on Noometry and Qwen3 14B has 12.