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

# Cerebras

> Use Cerebras high-speed inference with Agno agents.

[Cerebras Inference](https://inference-docs.cerebras.ai/introduction) provides high-speed, low-latency AI model inference powered by Cerebras Wafer-Scale Engines and CS-3 systems. Agno integrates directly with the Cerebras Python SDK, allowing you to use state-of-the-art Llama models with a simple interface.

## Prerequisites

To use Cerebras with Agno, you need to:

1. **Install the required packages:**

   ```shell theme={null}
   uv pip install cerebras-cloud-sdk
   ```

2. **Set your API key:**
   The Cerebras SDK expects your API key to be available as an environment variable:
   ```shell theme={null}
   export CEREBRAS_API_KEY=your_api_key_here
   ```

## Basic Usage

Here's how to use a Cerebras model with Agno:

```python theme={null}
from agno.agent import Agent
from agno.models.cerebras import Cerebras

agent = Agent(
    model=Cerebras(id="llama-4-scout-17b-16e-instruct"),
    markdown=True,
)

# Print the response in the terminal
agent.print_response("write a two sentence horror story")
```

## Supported Models

Cerebras currently supports the following models (see [docs](https://inference-docs.cerebras.ai/introduction) for the latest list):

| Model Name                      | Model ID                       | Parameters  | Knowledge     |
| ------------------------------- | ------------------------------ | ----------- | ------------- |
| Llama 4 Scout                   | llama-4-scout-17b-16e-instruct | 109 billion | August 2024   |
| Llama 3.1 8B                    | llama3.1-8b                    | 8 billion   | March 2023    |
| Llama 3.3 70B                   | llama-3.3-70b                  | 70 billion  | December 2023 |
| DeepSeek R1 Distill Llama 70B\* | deepseek-r1-distill-llama-70b  | 70 billion  | December 2023 |

\* DeepSeek R1 Distill Llama 70B is available in private preview.

## Parameters

| Parameter               | Type                              | Default                            | Description                                                                           |
| ----------------------- | --------------------------------- | ---------------------------------- | ------------------------------------------------------------------------------------- |
| `id`                    | `str`                             | `"llama-4-scout-17b-16e-instruct"` | The id of the Cerebras model to use                                                   |
| `name`                  | `str`                             | `"Cerebras"`                       | The name of the model                                                                 |
| `provider`              | `str`                             | `"Cerebras"`                       | The provider of the model                                                             |
| `parallel_tool_calls`   | `Optional[bool]`                  | `None`                             | Whether to run tool calls in parallel (automatically set to False for llama-4-scout)  |
| `max_completion_tokens` | `Optional[int]`                   | `None`                             | Maximum number of completion tokens to generate                                       |
| `repetition_penalty`    | `Optional[float]`                 | `None`                             | Penalty for repeating tokens (higher values reduce repetition)                        |
| `temperature`           | `Optional[float]`                 | `None`                             | Controls randomness in the model's output (0.0 to 2.0)                                |
| `top_p`                 | `Optional[float]`                 | `None`                             | Controls diversity via nucleus sampling (0.0 to 1.0)                                  |
| `top_k`                 | `Optional[int]`                   | `None`                             | Controls diversity via top-k sampling                                                 |
| `strict_output`         | `bool`                            | `True`                             | Controls schema adherence for structured outputs                                      |
| `extra_headers`         | `Optional[Any]`                   | `None`                             | Additional headers to include in requests                                             |
| `extra_query`           | `Optional[Any]`                   | `None`                             | Additional query parameters to include in requests                                    |
| `extra_body`            | `Optional[Any]`                   | `None`                             | Additional body parameters to include in requests                                     |
| `request_params`        | `Optional[Dict[str, Any]]`        | `None`                             | Additional parameters to include in the request                                       |
| `api_key`               | `Optional[str]`                   | `None`                             | The API key for authenticating with Cerebras (defaults to CEREBRAS\_API\_KEY env var) |
| `base_url`              | `Optional[Union[str, httpx.URL]]` | `None`                             | The base URL for the Cerebras API                                                     |
| `timeout`               | `Optional[float]`                 | `None`                             | Request timeout in seconds                                                            |
| `max_retries`           | `Optional[int]`                   | `None`                             | Maximum number of retries for failed requests                                         |
| `default_headers`       | `Optional[Any]`                   | `None`                             | Default headers to include in all requests                                            |
| `default_query`         | `Optional[Any]`                   | `None`                             | Default query parameters to include in all requests                                   |
| `http_client`           | `Optional[httpx.Client]`          | `None`                             | HTTP client instance for making requests                                              |
| `client_params`         | `Optional[Dict[str, Any]]`        | `None`                             | Additional parameters for client configuration                                        |
| `client`                | `Optional[CerebrasClient]`        | `None`                             | A pre-configured instance of the Cerebras client                                      |
| `async_client`          | `Optional[AsyncCerebrasClient]`   | `None`                             | A pre-configured instance of the async Cerebras client                                |

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

## Structured Outputs

The Cerebras model supports structured outputs using JSON schema:

```python theme={null}
from agno.agent import Agent
from agno.models.cerebras import Cerebras
from pydantic import BaseModel
from typing import List

class MovieScript(BaseModel):
    setting: str
    characters: List[str]
    plot: str

agent = Agent(
    model=Cerebras(id="llama-4-scout-17b-16e-instruct"),
    response_format=MovieScript,
)
```

## Resources

* [Cerebras Inference Documentation](https://inference-docs.cerebras.ai/introduction)
* [Cerebras API Reference](https://inference-docs.cerebras.ai/api-reference/chat-completions)

### SDK Examples

* View more examples [here](/models/providers/gateways/cerebras/usage/basic-stream).