Two leading open-source LLMs compared
Llama 3.1 is generally better for most use cases due to superior instruction following and longer context. Mistral wins on speed and licensing.
Choose Llama 3 if you need the best quality, long context, or aren't concerned about commercial licensing.
Choose Mistral if you need Apache 2.0 licensing, faster inference, or have limited VRAM.
Llama 3 and Mistral are the two most popular open-weight LLM families. Both run great locally, but excel in different areas. Here's how they compare.
| Specification | Llama 3.1 8B | Mistral 7B |
|---|---|---|
| Developer | Meta | Mistral AI |
| Parameters | 8B | 7B |
| Context Length | 128K | 32K |
| VRAM (Minimum) | 8GB (Q4) | 6GB (Q4) |
| VRAM (Recommended) | 12GB | 8GB |
| Release Date | July 2024 | September 2023 |
| License | Llama 3.1 Community License | Apache 2.0 |
| Category | Llama 3.1 8B | Mistral 7B | Winner |
|---|---|---|---|
| MMLU (Knowledge) | 69.4% | 62.5% | Llama 3.1 8B |
| HumanEval (Coding) | 72.6% | 56.1% | Llama 3.1 8B |
| GSM8K (Math) | 84.5% | 74.4% | Llama 3.1 8B |
| Inference Speed | ~60 tok/s | ~80 tok/s | Mistral 7B |
| VRAM Usage (Q4) | ~6GB | ~5GB | Mistral 7B |
Check our GPU buying guides to find the right hardware for running LLMs locally.