Side-by-side comparison of Gemma 4 E4B Instruct (Google DeepMind · United States) and Mistral Nemo (Mistral AI · France) for self-hosted deployment of the open-weight model. Gemma 4 E4B Instruct is rated conditional; Mistral Nemo is EU-ready. They part ways on training data: Gemma 4 E4B Instruct is "Domain-level summary", Mistral Nemo is "Undisclosed corpus".
| Field | ||
|---|---|---|
| Summary | ||
| Verdict | Conditional Based on published licence terms, Gemma 4 E4B is an edge-optimised multimodal variant under pure Apache 2.0 with no prohibited-use carve-outs. Audio input (30s) and on-device deployment push GDPR biometric, AI Act emotion-recognition, and Art. 25 data-protection-by-design obligations entirely onto the integrator with no Google-side telemetry or kill-switch. | 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 | 2026-04-17 | 2026-05-19 |
| Open-weight | ||
| Licence | Apache 2.0 | Apache 2.0 |
| Commercial use | Unrestricted | Unrestricted |
| Training data | Domain-level summary | Undisclosed corpus |
| Origin | United States | EU (France) |
| Performance & pricing? | ||
| Quality index | 15/100 | — |
| Speed | — | — |
| Blended price | — | — |
| Context window | — | — |
| Evidence | ||
| Sources | ||
No overlapping sources between the two entries.