Mistral AI · llama
Can I run mistrallite?
MistralLite is a fine-tuned model based on Mistral with enhanced capabilities of processing long contexts.
Parameter counts and memory belong to each build below. A family can contain several sizes and tasks; fitting in memory is not a quality ranking.
Calculate memory for a build and contextmistrallite system requirements
Memory needed at 4K context, counting model weights, KV cache, compute buffers and runtime overhead. Download sizes come from the official Ollama registry.
| Build | Quantization | Download | Memory needed |
|---|---|---|---|
| mistrallite:7b7B parameters (tag)32K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q4_0 | 3.8 GB | ~5.0 GB |
| mistrallite:7b-v0.1-q4_K_M7B parameters (tag)32K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q4_K_M | 4.1 GB | ~5.3 GB |
| mistrallite:7b-v0.1-q5_K_M7B parameters (tag)32K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q5_K_M | 4.8 GB | ~6.1 GB |
| mistrallite:7b-v0.1-q6_K7B parameters (tag)32K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q6_K | 5.5 GB | ~6.9 GB |
| mistrallite:7b-v0.1-q8_07B parameters (tag)32K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q8_0 | 7.2 GB | ~8.6 GB |
| mistrallite:7b-v0.1-fp167B parameters (tag)32K documented maximum contextBuild sourceCatalog checked 2026-10-13 | F16 | 13.5 GB | ~15.5 GB |
Showing the 6 smallest non-alias builds. Choose any build and change the context. A context above the build's documented maximum is a hypothetical calculation, not a supported setting.
How to run mistrallite locally
- 1.Install Ollama for Windows, macOS or Linux.
- 2.Download this exact build in a terminal:
ollama pull mistrallite:7b - 3.Check the source for the build's task. For text generation, run
ollama run mistrallite:7b. Base/text builds may need a prompt template; an instruct build is usually the appropriate starting point for a conversation.
Frequently asked questions about mistrallite
- How much VRAM do I need to run mistrallite?
- At 4K context, the smallest published build of mistrallite (Q4_0) needs roughly 5.0 GB of GPU memory once weights, KV cache, compute buffers and runtime overhead are counted. Bigger quantizations and longer context windows need more. It can also run partly or entirely on the CPU using system RAM, more slowly.
- Can I run mistrallite without a dedicated GPU?
- A supported CPU runtime can use system RAM. The smallest listed build needs an estimated 5.0 GB at 4K context, plus headroom for your operating system. Check the build's runtime requirements. We have not measured its speed on your CPU.
- How big is the mistrallite download?
- The smallest published build is 3.8 GB. There are 6 builds in total, the largest being 13.5 GB. Leave some extra free disk space beyond the download itself.
- How do I run mistrallite locally?
- Install Ollama, then download a specific build with "ollama pull mistrallite:7b". For a build that supports text generation, use ollama run with the same tag. Check the model source for its task and prompt format.
Will mistrallite run on your PC?
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Compare with similar models
Or start from your memory: 8 GB VRAM, 12 GB VRAM, 16 GB VRAM, 24 GB VRAM or a 16 GB Mac.
Model data from the official Ollama registry · verified 13/10/2026