Side-by-side comparison of DeepSeek R1 (DeepSeek · China) and OLMo 2 32B (AllenAI · USA) for self-hosted deployment of the open-weight model. DeepSeek R1 is rated conditional; OLMo 2 32B is EU-ready. They part ways on licence: DeepSeek R1 is "MIT", OLMo 2 32B is "Apache 2.0".
| Field | ||
|---|---|---|
| Summary | ||
| Verdict | Conditional Frontier reasoning model at o1-class performance. MIT licence makes weights legally clean. Same Chinese-origin alignment/supply-chain considerations as DeepSeek V3. Distilled Qwen/Llama versions inherit their base licence. | EU-ready Fully open model: weights, training data (Dolma 2), training code, checkpoints, and logs all published. Apache 2.0 across the board. Strongest choice when AI Act transparency obligations matter. |
| Last reviewed | 2026-04-15 | 2026-04-15 |
| Open-weight | ||
| Licence | MIT | Apache 2.0 |
| Commercial use | Yes | Yes |
| Training data | Undisclosed | Disclosed |
| Origin | China | USA |
| Performance & pricing? | ||
| Quality index | 27/100 | 11/100 |
| Speed | — | — |
| Blended price | $2.36/M | — |
| Context window | — | — |
| Evidence | ||
| Sources | ||
No overlapping sources between the two entries.