Llama vs Mistral
Both are open and self-hostable; Llama wins on ecosystem breadth and, with Scout's 10M window, on raw context. Mistral wins on efficiency and European data governance, and Medium 3.5 is the more recent release of the two. For most on-prem work the deciding factor is the governance story rather than the benchmark.
| Llama | Mistral | |
|---|---|---|
| Provider | Meta | Mistral AI |
| Current release | Llama 4 | Medium 3.5 |
| Tier | Open weights | Open weights |
| Context | 10M | 256K |
| Cost | Free tier | Low cost |
| Modalities | text, vision | text, vision |
| Open weights | Yes | Yes |
Cost is a tier, not a quote, providers change prices often. Check Meta and Mistral AI before you commit. Last updated 2026-09-04.
Which one to pick
LlamaMeta · Llama 4
The widest open ecosystem, tooling and fine-tunes, though Meta's newer open work ships as Muse
Reach for it when- The widest selection of tooling and community fine-tunes
- You want the most-documented path
MistralMistral AI · Medium 3.5
Efficient European open models for building without heavy lock-in
Reach for it when- On-prem deployments with EU data requirements
- A more recently updated model with a smaller serving footprint