> ## Documentation Index
> Fetch the complete documentation index at: https://docs-v1.agno.com/llms.txt
> Use this file to discover all available pages before exploring further.

# DeepSeek

> Learn how to use DeepSeek models in Agno.

DeepSeek is a platform for providing endpoints for Large Language models.
See their library of models [here](https://api-docs.deepseek.com/quick_start/pricing).

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

* `deepseek-chat` model is good for most basic use-cases.
* `deepseek-reasoner` model is good for complex reasoning and multi-step tasks.

DeepSeek does not have rate limits. See their [docs](https://api-docs.deepseek.com/quick_start/rate_limit) for information about how to deal with slower responses during high traffic.

## Authentication

Set your `DEEPSEEK_API_KEY` environment variable. Get your key from [here](https://platform.deepseek.com/api_keys).

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

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

## Example

Use `DeepSeek` with your `Agent`:

<CodeGroup>
  ```python agent.py theme={null}
  from agno.agent import Agent, RunResponse
  from agno.models.deepseek import DeepSeek

  agent = Agent(model=DeepSeek(), markdown=True)

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

  ```
</CodeGroup>

<Note> View more examples [here](../examples/models/deepseek). </Note>

## Params

<Snippet file="model-deepseek-params.mdx" />

`DeepSeek` also supports the params of [OpenAI](/reference/models/openai).