Side-by-side comparison of Mistral Nemo (Mistral AI · France) and Qwen3-8B (Alibaba Cloud (Qwen) · China) for self-hosted deployment of the open-weight model. Mistral Nemo is rated EU-ready; Qwen3-8B is conditional. They part ways on training data: Mistral Nemo is "Undisclosed corpus", Qwen3-8B is "Token count only".
| Field | ||
|---|---|---|
| Summary | ||
| Verdict | 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. | Conditional Based on published licence terms, Qwen3-8B is released under standard Apache 2.0 with no field-of-use carve-outs, making self-hosted commercial deployment viable. Training-data disclosure is limited to a token count and Chinese origin creates EU AI Act Art. 53 transparency and data-transfer risks that deployers should document. |
| Last reviewed | 2026-05-19 | 2026-04-17 |
| Open-weight | ||
| Licence | Apache 2.0 | Apache 2.0 |
| Commercial use | Unrestricted | Unrestricted |
| Training data | Undisclosed corpus | Token count only |
| Origin | EU (France) | China (Hangzhou) |
| Performance & pricing? | ||
| Quality index | — | 11/100 |
| Speed | — | 86 tok/s |
| Blended price | — | $0.31/M |
| Context window | — | — |
| Evidence | ||
| Sources | ||
No overlapping sources between the two entries.