Side-by-side comparison of DeepSeek-V4-Pro (DeepSeek · China) and Llama 3.1 Nemotron 70B (NVIDIA · USA) for self-hosted deployment of the open-weight model. DeepSeek-V4-Pro is rated conditional; Llama 3.1 Nemotron 70B is conditional. They part ways on licence: DeepSeek-V4-Pro is "MIT", Llama 3.1 Nemotron 70B is "Llama community".
| Field | ||
|---|---|---|
| Summary | ||
| Verdict | Conditional Per the published LICENSE file, DeepSeek-V4-Pro ships under MIT with no commercial restrictions, so the weights themselves are deployable. The caveats are non-EU jurisdiction and a training corpus described only by aggregate token count (32T+) without a dataset list — both should be documented in any GDPR or AI Act compliance file before regulated use. | Conditional NVIDIA's Llama 3.1 fine-tune with custom RLHF. Inherits Llama 3.1 Community License terms. Strong conversational quality; useful default when you want Llama behaviour with NVIDIA's alignment. |
| Last reviewed | 2026-04-28 | 2026-04-15 |
| Open-weight | ||
| Licence | MIT | Llama community |
| Commercial use | Unrestricted | With caps |
| Training data | Categories only | Partial |
| Origin | China | USA |
| Performance & pricing? | ||
| Quality index | 52/100 | 13/100 |
| Speed | 36 tok/s | 42 tok/s |
| Blended price | $2.17/M | $1.20/M |
| Context window | — | — |
| Evidence | ||
| Sources | ||
No overlapping sources between the two entries.