Side-by-side comparison of DeepSeek-V4-Flash (DeepSeek · China) and Mistral Nemo (Mistral AI · France) for self-hosted deployment of the open-weight model. DeepSeek-V4-Flash is rated conditional; Mistral Nemo is EU-ready. They part ways on licence: DeepSeek-V4-Flash is "MIT", Mistral Nemo is "Apache 2.0".
| Field | ||
|---|---|---|
| Summary | ||
| Verdict | Conditional DeepSeek-V4-Flash is the smaller-active sibling of V4-Pro under the same MIT terms — permissive on the weights, but the China-based vendor and undocumented training corpus mean any EU deployment still needs a self-hosted topology and a deployer-side GPAI documentation file under AI Act Article 53. | EU-ready A 12B model from Paris-based Mistral AI, co-trained with NVIDIA and shipped under Apache 2.0 with a 128k context window and strong coverage of major EU languages. EU-headquartered vendor plus a fully permissive licence make this one of the cleanest open-weight choices for organisations prioritising AI Act and GDPR alignment, with the main caveat being the usual lack of detail on the training corpus. |
| Last reviewed | 2026-04-28 | 2026-05-19 |
| Open-weight | ||
| Licence | MIT | Apache 2.0 |
| Commercial use | Unrestricted | Unrestricted |
| Training data | Categories only | Undisclosed corpus |
| Origin | China | EU (France) |
| Performance & pricing? | ||
| Quality index | 47/100 | — |
| Speed | 79 tok/s | — |
| Blended price | $0.17/M | — |
| Context window | — | — |
| Evidence | ||
| Sources | ||
No overlapping sources between the two entries.