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.
| Specifiche | Mistral NeMo 12B | Gemma 3 12B |
|---|---|---|
| Sviluppatore | Mistral AI | |
| Tipo | LLM (densa) | LLM (multimodale) |
| Parametri | 12 miliardi | 12 miliardi |
| Finestra di contesto | 128K | 128K |
| Modalità | Testo → Testo | Testo, immagine → testo |
| Licenza | Apache 2.0 (open) | Gemma (open) |
| Pesi aperti | ✅ Sì | ✅ Sì |
| Input price ($/1M) | $0.02 | $0.05 |
| Output price ($/1M) | $0.04 | $0.15 |
| VRAM (4-bit) | ~7,5 GB | ~8 GB |
| Min GPU (local) | RTX 4070 12 GB / RTX 3060 | RTX 4070 12 GB |
| Rilasciato | 2024 | 2025 |
Key differences
- Costo: Mistral NeMo 12B is 200% cheaper than Gemma 3 12B on a blended-token basis.
- Apertura: 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).
Quale scegliere?
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 calcolatore di VRAM · browse all 30+ models.
All specs and prices are pulled live from our database di modelli AI and kept current. Compare either model against others, or estimate your own monthly spend with the free calculators above.