Model weights
We open-source both pre-trained models and instruction-tuned models. These models are not tuned for safety as we want to empower users to test and refine moderation based on their use cases. For safer models, follow our guardrailing tutorial.
License
- Mistral 7B, Mixtral 8x7B, Mixtral 8x22B, Codestral Mamba, Mathstral, Mistral Nemo, and Pixtral 12B are under Apache 2 License, which permits their use without any constraints.
- Codestral is under Mistral AI Non-Production (MNPL) License.
- Ministral 8B, Mistral Large, Pixtral Large and Mistral Small are under Mistral Research License.
note
If you are interested in purchasing a commercial license for our models, please contact our team
Downloading
| Model | Download links | Features |
|---|---|---|
| Mistral-7B-v0.1 | Hugging Face raw_weights (md5sum: 37dab53973db2d56b2da0a033a15307f) | - 32k vocabulary size - Rope Theta = 1e4 - With sliding window |
| Mistral-7B-Instruct-v0.2 | Hugging Face raw_weights (md5sum: fbae55bc038f12f010b4251326e73d39) | - 32k vocabulary size - Rope Theta = 1e6 - No sliding window |
| Mistral-7B-v0.3 | Hugging Face raw_weights (md5sum: 0663b293810d7571dad25dae2f2a5806) | - Extended vocabulary to 32768 |
| Mistral-7B-Instruct-v0.3 | Hugging Face raw_weights (md5sum: 80b71fcb6416085bcb4efad86dfb4d52) | - Extended vocabulary to 32768 - Supports v3 Tokenizer - Supports function calling |
| Mixtral-8x7B-v0.1 | Hugging Face | - 32k vocabulary size - Rope Theta = 1e6 |
| Mixtral-8x7B-Instruct-v0.1 | Hugging Face raw_weights (md5sum: 8e2d3930145dc43d3084396f49d38a3f) | - 32k vocabulary size - Rope Theta = 1e6 |
| Mixtral-8x7B-v0.3 | Updated model coming soon! | - Extended vocabulary to 32768 - Supports v3 Tokenizer |
| Mixtral-8x7B-Instruct-v0.3 | Updated model coming soon! | - Extended vocabulary to 32768 - Supports v3 Tokenizer - Supports function calling |
| Mixtral-8x22B-v0.1 | Hugging Face raw_weights (md5sum: 0535902c85ddbb04d4bebbf4371c6341) | - 32k vocabulary size |
| Mixtral-8x22B-Instruct-v0.1/ Mixtral-8x22B-Instruct-v0.3 | Hugging Face raw_weights (md5sum: 471a02a6902706a2f1e44a693813855b) | - 32768 vocabulary size |
| Mixtral-8x22B-v0.3 | raw_weights (md5sum: a2fa75117174f87d1197e3a4eb50371a) | - 32768 vocabulary size - Supports v3 Tokenizer |
| Codestral-22B-v0.1 | Hugging Face raw_weights (md5sum: 1ea95d474a1d374b1d1b20a8e0159de3) | - 32768 vocabulary size - Supports v3 Tokenizer |
| Codestral-Mamba-7B-v0.1 | Hugging Face raw_weights (md5sum: d3993e4024d1395910c55db0d11db163) | - 32768 vocabulary size - Supports v3 Tokenizer |
| Mathstral-7B-v0.1 | Hugging Face raw_weights (md5sum: 5f05443e94489c261462794b1016f10b) | - 32768 vocabulary size - Supports v3 Tokenizer |
| Mistral-Nemo-Base-2407 | Hugging Face raw_weights (md5sum: c5d079ac4b55fc1ae35f51f0a3c0eb83) | - 131k vocabulary size - Supports v3 tekken.json tokenizer |
| Mistral-Nemo-Instruct-2407 | Hugging Face raw_weights (md5sum: 296fbdf911cb88e6f0be74cd04827fe7) | - 131k vocabulary size - Supports v3 tekken.json tokenizer - Supports function calling |
| Mistral-Large-Instruct-2407 | Hugging Face raw_weights (md5sum: fc602155f9e39151fba81fcaab2fa7c4) | - 32768 vocabulary size - Supports v3 Tokenizer - Supports function calling |
| Pixtral-2409 | Hugging Face | - 131k vocabulary size - Supports v3 tekken.json tokenizer - Supports function calling |
| Mistral-Small-Instruct-2409 | Hugging Face | - 32768 vocabulary size - Supports v3 Tokenizer - Supports function calling |
| Ministral-8B-Instruct-2410 | Hugging Face | - 131k vocabulary size - Supports v3 tekken.json tokenizer - Supports function calling |
| Mistral-Large-Instruct-2411 | Hugging Face | - 32768 vocabulary size - Supports v7 tokenizer - Supports function calling |
| Pixtral-Large-Instruct-2411 | Hugging Face | - 32768 vocabulary size - Supports v7 tokenizer - Supports function calling |
Sizes
| Name | Number of parameters | Number of active parameters | Min. GPU RAM for inference (GB) |
|---|---|---|---|
| Mistral-7B-v0.3 | 7.3B | 7.3B | 16 |
| Mixtral-8x7B-v0.1 | 46.7B | 12.9B | 100 |
| Mixtral-8x22B-v0.3 | 140.6B | 39.1B | 300 |
| Codestral-22B-v0.1 | 22.2B | 22.2B | 60 |
| Codestral-Mamba-7B-v0.1 | 7.3B | 7.3B | 16 |
| Mathstral-7B-v0.1 | 7.3B | 7.3B | 16 |
| Mistral-Nemo-Instruct-2407 | 12B | 12B | 28 - bf16 16 - fp8 |
| Mistral-Large-Instruct-2407 | 123B | 123B | 250 |
| Pixtral-2409 | 12B | 12B | 28 - bf16 16 - fp8 |
| Mistral-Small-2409 | 22B | 22B | 60 |
| Ministral-8B-2410 | 8B | 8B | 24 |
| Mistral-Large-Instruct-2411 | 123B | 123B | 250 |
| Pixtral-Large-Instruct-2411 | 124B | 124B | 250 |
How to run?
Check out mistral-inference, a Python package for running our models. You can install mistral-inference by
pip install mistral-inference
To learn more about how to use mistral-inference, take a look at the README and dive into this colab notebook to get started:
