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.
| Spezifikation | Mistral NeMo 12B | Gemma 3 12B |
|---|---|---|
| Entwickler | Mistral AI | |
| Typ | LLM (dicht) | LLM (multimodal) |
| Parameter | 12 Mrd. | 12 Mrd. |
| Kontextfenster | 128K | 128K |
| Modalität | Text → Text | Text, Bild → Text |
| Lizenz | Apache 2.0 (offen) | Gemma (offen) |
| Offene Gewichte | ✅ Ja | ✅ Ja |
| Input price ($/1M) | $0.02 | $0.05 |
| Output price ($/1M) | $0.04 | $0.15 |
| VRAM (4-Bit) | ca. 7,5 GB | ~8 GB |
| Min GPU (local) | RTX 4070 12 GB / RTX 3060 | RTX 4070 mit 12 GB |
| Veröffentlicht | 2024 | 2025 |
Key differences
- Kosten: Mistral NeMo 12B is 200% cheaper than Gemma 3 12B on a blended-token basis.
- Offenheit: 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).
Welches Modell sollten Sie wählen?
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 VRAM-Rechner · browse all 30+ models.
All specs and prices are pulled live from our Datenbank für KI-Modelle and kept current. Compare either model against others, or estimate your own monthly spend with the free calculators above.