Model comparison
DeepSeek-V2 (MoE-236B, May 2024) vs o1-pro
o1-pro has enough public results to be ranked (#264); DeepSeek-V2 (MoE-236B, May 2024) does not yet, so treat this comparison as directional.
Last verified . 0 shared benchmarks.
Summary
- DeepSeek-V2 (MoE-236B, May 2024) has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V2 (MoE-236B, May 2024) | o1-pro | |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 39.7 | 31.2 |
| Released | 2024-05-07 | 2025-03-19 |
| Weights | Open | Proprietary |
| Context window | — | 200K |
| Max output | — | 100K |
| Input $ / M tokens | — | $150 |
| Output $ / M tokens | — | $600 |
| Results tracked | 10 | 3 |
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Category by category
Coding Not comparable
DeepSeek-V2 (MoE-236B, May 2024): 39.8 (#141), o1-pro: —
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | o1-pro |
|---|---|---|
| BigCodeBench Instruct | 48.9% | — |
| BigCodeBench Complete | 59.4% | — |
Reasoning Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, o1-pro: 20.2 (#223)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | o1-pro |
|---|---|---|
| ARC-AGI-1 | — | 23.3% |
| EnigmaEval | — | 6.1% |
| BIG-Bench Hard | 78.8% | — |
| Epoch Capabilities Index | 124.78 | — |
| HellaSwag | 87.1% | — |
| PIQA | 83.9% | — |
| WinoGrande | 86.3% | — |
Knowledge Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, o1-pro: 29.3 (#227)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | o1-pro |
|---|---|---|
| Humanity's Last Exam | — | 8.1% |
| ARC (AI2) Challenge | 92.2% | — |
| MMLU | 78.4% | — |
| TriviaQA | 80% | — |
Frequently asked questions
Is DeepSeek-V2 (MoE-236B, May 2024) better than o1-pro?
o1-pro has enough public results to be ranked (#264); DeepSeek-V2 (MoE-236B, May 2024) does not yet, so treat this comparison as directional.
How many benchmarks do DeepSeek-V2 (MoE-236B, May 2024) and o1-pro share?
0 benchmarks have published results for both models. DeepSeek-V2 (MoE-236B, May 2024) has 10 scored results on Noometry and o1-pro has 3.