Side-by-side comparison of DeepSeek R1 (DeepSeek · China) and DeepSeek V3.2 (DeepSeek · China) for self-hosted deployment of the open-weight model. DeepSeek R1 is rated conditional; DeepSeek V3.2 is conditional. On the four sovereignty dimensions we track, they score identically — the difference is in context and org posture.
| 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. | Conditional 685B successor to V3 with DeepSeek Sparse Attention for long context, scalable RL for agentic tasks. Vendor claims parity with GPT-5 (Speciale variant exceeds). MIT licence keeps weights clean; Chinese-origin considerations unchanged. |
| Last reviewed | 2026-04-15 | 2026-04-15 |
| Open-weight | ||
| Licence | MIT | MIT |
| Commercial use | Yes | Yes |
| Training data | Undisclosed | Undisclosed |
| Origin | China | China |
| Performance & pricing? | ||
| Quality index | 27/100 | 32/100 |
| Speed | — | 32 tok/s |
| Blended price | $2.36/M | $0.32/M |
| Context window | — | — |
| Evidence | ||
| Sources | ||
No overlapping sources between the two entries.