> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/brev/llms.txt.
> For full documentation content, see https://docs.nvidia.com/brev/llms-full.txt.

# Running Agents on Brev

> Deploy AI agents on NVIDIA Brev CPU instances for sandboxed code execution, web tasks, and more.

Deploy AI agents on Brev CPU instances for sandboxed execution environments. CPU instances provide isolated, cost-effective compute for agent workloads that don't require GPU acceleration.

## Prerequisites

* A Brev account ([sign up](https://brev.nvidia.com))
* Brev CLI installed ([Quickstart](/docs/getting-started/quickstart))

## Deploy an Agent Sandbox

### Option A: Deploy from a Launchable

Use a pre-built Launchable to get started quickly:

* **NemoClaw Agent** — the NVIDIA agent framework for tool-use and code execution
* **Generic Agent Sandbox** — a blank CPU sandbox for custom agent deployments

Browse available Launchables at [brev.nvidia.com](https://brev.nvidia.com/environment/new/public). Select a CPU instance type and deploy.

### Option B: Provision Manually

Create a CPU instance through the [Brev Console](https://brev.nvidia.com) or CLI:

```bash
brev create my-agent
```

Select a CPU instance type (no GPU) when prompted, or specify one in the [Brev Console](https://brev.nvidia.com).

### Connect and Verify

<Steps>
  <Step title="Connect to your instance">
    After the instance is running, connect with the CLI:

    ```bash
    brev shell my-agent
    ```
  </Step>

  <Step title="Verify the agent is running">
    Check that your agent process is active:

    ```bash
    # Check running processes
    ps aux | grep agent

    # Check Docker containers if using containerized agents
    docker ps
    ```
  </Step>
</Steps>

## CPU vs GPU for Agents

| Use Case                    | Recommended  | Why                               |
| --------------------------- | ------------ | --------------------------------- |
| Code execution / sandboxes  | CPU instance | No GPU needed, lower cost.        |
| Web browsing / scraping     | CPU instance | Network-bound, not compute-bound. |
| Tool use / API calls        | CPU instance | Minimal compute requirements.     |
| LLM inference (self-hosted) | GPU instance | Models require GPU acceleration.  |
| Vision / image processing   | GPU instance | GPU accelerates image operations. |
| Training / fine-tuning      | GPU instance | Requires GPU compute.             |

## What's Next?

<CardGroup cols={1}>
  <Card title="CPU Instances" icon="server" href="/concepts/cpu-instances">
    Learn about CPU instance lifecycle, supported types, and billing.
  </Card>

  <Card title="Launchables" icon="rocket" href="/concepts/launchables">
    Create and share one-click deployable agent environments.
  </Card>
</CardGroup>