> ## 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.

# Cerebras

> Learn how to use Cerebras models in Agno.

[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}
   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.

## Configuration Options

The `Cerebras` class accepts the following parameters:

| Parameter        | Type                       | Description                                               | Default      |
| ---------------- | -------------------------- | --------------------------------------------------------- | ------------ |
| `id`             | str                        | Model identifier (e.g., "llama-4-scout-17b-16e-instruct") | **Required** |
| `name`           | str                        | Display name for the model                                | "Cerebras"   |
| `provider`       | str                        | Provider name                                             | "Cerebras"   |
| `api_key`        | Optional\[str]             | API key (falls back to `CEREBRAS_API_KEY` env var)        | None         |
| `max_tokens`     | Optional\[int]             | Maximum tokens in the response                            | None         |
| `temperature`    | float                      | Sampling temperature                                      | 0.7          |
| `top_p`          | float                      | Top-p sampling value                                      | 1.0          |
| `request_params` | Optional\[Dict\[str, Any]] | Additional request parameters                             | None         |

## 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](../examples/models/cerebras).