Gemma 3 12B vs Mistral Nemo 12B
Size, context window, license, approximate VRAM and the minimum local hardware each model needs — computed from our catalog and compatibility engine, not benchmarks.
| Gemma 3 12B | Mistral Nemo 12B | |
|---|---|---|
| Parameters | 12B | 12B |
| Context window | 128K tokens | 128K tokens |
| License | Gemma Terms of Use | Apache-2.0 |
| ~VRAM @ 4-bit (Q4_K_M) | ~8 GB | ~8 GB |
| ~VRAM @ 8-bit (Q8_0) | ~13 GB | ~13 GB |
| Minimum device | NVIDIA GeForce RTX 3060 12GB | NVIDIA GeForce RTX 3060 12GB |
| Recommended device | Supermicro 8x H100 SuperServer | Supermicro 8x H100 SuperServer |
| Deployment | Local / on-prem | Local / on-prem |
| Capabilities | Vision, Multilingual, Long context | Tools, Multilingual, Long context |
Highlighted cells mark the lighter / longer / more permissive side per row, for local deployment. Informational rows have no winner.
Bottom line
Gemma 3 12B and Mistral Nemo 12B are the same size (~12B parameters), so their memory footprints are comparable. Both target a 128K context window. Mistral Nemo 12B's Apache-2.0 license is the more permissive of the two for commercial use. Both can start on a NVIDIA GeForce RTX 3060 12GB-class machine. Figures are approximate working-set estimates, not benchmarks — verify the exact release before committing hardware.
Pick Gemma 3 12B if everyday team assistant.
Pick Mistral Nemo 12B if you want the more permissive Apache-2.0 license.
16GB+ GPUs at 4-bit. A current mid-size generalist with long context and image input.
16GB+ GPUs at 4-bit. A 128K-context, openly-licensed mid-size model built with NVIDIA.
Run the winner on hardware you control
Pick the model that fits your footprint, then turn the right machine into a private AI Business OS — no per-seat data leaving your premises.