Mistral Nemo 12B
Mistral AI · Mistral
Built in partnership with NVIDIA and trained on a broad multilingual corpus, Nemo is Mistral's best model for non-English tasks across European and Asian languages. The 128K context window makes it practical for processing long documents locally.
Params
12B
License
Apache 2.0
Context
128K
Min VRAM
7 GB
Min RAM
16 GB
Tier
Standard
Run locally with Ollama
ollama run mistral-nemo:12bOnce running, Ollama exposes an OpenAI-compatible endpoint at localhost:11434/v1.
Will it run on my hardware?
Mistral Nemo 12B needs about 7 GB of fast memory at Q4. Here is what in our hardware database clears that bar.
Runs at full speed · 12
Runs, but slower on shared memory · 3
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Specifications
| Parameters | 12B |
|---|---|
| Context window | 128K |
| License | Apache 2.0 |
| Min VRAM (Q4) | 7 GB |
| Min RAM | 16 GB |
| Recommended tier | Standard |
| Best for | chatmultilingualanalysis |
Variants on Ollama
Ollama serves the Q4_K_M quantization by default. Higher-precision tags exist for users with more memory.
Mistral Nemo 12B
ollama run mistral-nemo:12bollama pull mistral-nemo:q8_0ollama pull mistral-nemo:fp16Exact quantization tags vary per model — run ollama show mistral-nemo or check the tags page for the full list.
Popularity trend (illustrative)
Illustrative adoption trend, not actual download counts. We do not publish a download number for any model because we have no honest source for it.
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