> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2-service-account.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Mistral

> Use Mistral models with Agno agents.

Mistral provides API endpoints for its large language models.
See their library of models [here](https://docs.mistral.ai/getting-started/models/models_overview/).

We recommend experimenting to find the best-suited model for your use-case. Here are some general recommendations:

* `codestral` model is good for code generation and editing.
* `mistral-large-latest` model is good for most use-cases.
* `open-mistral-nemo` is a free model that is good for most use-cases.
* `pixtral-12b-2409` is a vision model that is good for OCR, transcribing documents, and image comparison. It is not always reliable at tool calling.

Mistral has tier-based rate limits. See the [tier docs](https://docs.mistral.ai/deployment/laplateforme/tier/).

## Installation

```bash theme={null}
uv pip install -U mistralai agno
```

## Authentication

Set your `MISTRAL_API_KEY` environment variable. Get your key from [here](https://console.mistral.ai/api-keys/).

<CodeGroup>
  ```bash Mac theme={null}
  export MISTRAL_API_KEY=***
  ```

  ```bash Windows theme={null}
  setx MISTRAL_API_KEY ***
  ```
</CodeGroup>

## Example

Use `MistralChat` with your `Agent`:

<CodeGroup>
  ```python agent.py theme={null}
  import os

  from agno.agent import Agent
  from agno.models.mistral import MistralChat

  mistral_api_key = os.getenv("MISTRAL_API_KEY")

  agent = Agent(
      model=MistralChat(
          id="mistral-large-latest",
          api_key=mistral_api_key,
      ),
      markdown=True
  )

  # Print the response in the terminal
  agent.print_response("Share a 2 sentence horror story.")

  ```
</CodeGroup>

<Note> View more examples [here](/models/providers/native/mistral/usage/basic). </Note>

## Params

| Parameter        | Type                       | Default                  | Description                                                     |
| ---------------- | -------------------------- | ------------------------ | --------------------------------------------------------------- |
| `id`             | `str`                      | `"mistral-large-latest"` | The id of the Mistral model to use                              |
| `name`           | `str`                      | `"MistralChat"`          | The name of the model                                           |
| `provider`       | `str`                      | `"Mistral"`              | The provider of the model                                       |
| `temperature`    | `Optional[float]`          | `None`                   | Controls randomness in the model's output                       |
| `max_tokens`     | `Optional[int]`            | `None`                   | Maximum number of tokens to generate                            |
| `top_p`          | `Optional[float]`          | `None`                   | Controls diversity via nucleus sampling                         |
| `random_seed`    | `Optional[int]`            | `None`                   | Random seed for reproducibility                                 |
| `safe_mode`      | `bool`                     | `False`                  | Enable safe mode content filtering                              |
| `safe_prompt`    | `bool`                     | `False`                  | Prepend a safety prompt to all requests                         |
| `request_params` | `Optional[Dict[str, Any]]` | `None`                   | Additional parameters for the request                           |
| `api_key`        | `Optional[str]`            | `None`                   | The API key for Mistral (defaults to `MISTRAL_API_KEY` env var) |
| `endpoint`       | `Optional[str]`            | `None`                   | Custom endpoint for the Mistral API                             |
| `max_retries`    | `Optional[int]`            | `None`                   | Maximum number of retries for API requests                      |
| `timeout`        | `Optional[int]`            | `None`                   | Request timeout in seconds                                      |
| `client_params`  | `Optional[Dict[str, Any]]` | `None`                   | Additional parameters for client configuration                  |
| `mistral_client` | `Optional[Mistral]`        | `None`                   | A pre-configured Mistral client instance to use                 |

`MistralChat` is a subclass of the [Model](/reference/models/model) class and has access to the same params.