Mistral NeMo 12B vs Gemma 3 12B — two 12B workhorses for local inference. Below is the full side-by-side: specifications, API pricing, context window, local hardware requirements, and a clear, data-driven recommendation on which to pick.
| Spécifications | Mistral NeMo 12B | Gemma 3 12B |
|---|---|---|
| Développeur | Mistral AI | |
| Type | LLM (dense) | LLM (multimodal) |
| Paramètres | 12 milliards | 12 milliards |
| Fenêtre de contexte | 128 K | 128 K |
| Modalité | Texte → Texte | Texte, image → texte |
| Licence | Apache 2.0 (ouverte) | Gemma (ouverte) |
| Poids ouverts | ✅ Oui | ✅ Oui |
| Input price ($/1M) | $0.02 | $0.05 |
| Output price ($/1M) | $0.04 | $0.15 |
| VRAM (4 bits) | ~7,5 Go | ~8 Go |
| Min GPU (local) | RTX 4070 12 Go / RTX 3060 | RTX 4070 12 Go |
| Date de sortie | 2024 | 2025 |
Key differences
- Coût : Mistral NeMo 12B is 200% cheaper than Gemma 3 12B on a blended-token basis.
- Ouverture : both are open-weight, so either can be self-hosted or fine-tuned. Compare their VRAM needs above to see what your GPU can run.
- Run Mistral NeMo 12B locally: ~~7.5 GB at 4-bit (min RTX 4070 12GB / RTX 3060).
- Run Gemma 3 12B locally: ~~8 GB at 4-bit (min RTX 4070 12GB).
Lequel choisir ?
Choose Mistral NeMo 12B if you want the lower per-token cost for high-volume workloads.
Choose Gemma 3 12B if it fits your existing stack or you prefer Google.
→ Estimate real costs in the API cost calculator · check local hardware in the calculateur de VRAM · browse all 30+ models.
All specs and prices are pulled live from our base de données de modèles IA and kept current. Compare either model against others, or estimate your own monthly spend with the free calculators above.