***

title: Quickstart
description: Get your first GPU instance running with the NVIDIA Brev quickstart guide.
---------------------------------------------------------------------------------------

NVIDIA’s Brev platform simplifies GPU access by offering virtual machine instances with various GPU types. Instead of being limited to one cloud provider, Brev pulls resources from multiple providers, helping you find the right GPU setup for your workload.

Brev allows you to create, manage, and access your GPU instances.

This guide will help you build a fully configured GPU development environment and launch your first instance in three steps.

## Prerequisites

* A Brev account: [sign up at brev.nvidia.com](https://brev.nvidia.com)
* A terminal: (macOS Terminal, Linux shell, or Windows WSL)
* For macOS: [Homebrew](https://brew.sh) installed

<Steps>
  <Step title="Install the Brev CLI">
    The Brev CLI manages your GPU instances from the terminal. Choose from one of the following platforms:

    <CodeGroup>
      ```bash macOS
      # Install with Homebrew
      brew install brevdev/homebrew-brev/brev

      # Verify installation
      brev --version
      ```

      ```bash Linux
      # Download and run the installer
      sudo bash -c "$(curl -fsSL https://raw.githubusercontent.com/brevdev/brev-cli/main/bin/install-latest.sh)"

      # Verify installation
      brev --version
      ```

      ```powershell Windows
      # First, install WSL with Ubuntu (run in PowerShell as admin)
      wsl --install -d Ubuntu-22.04

      # Restart your computer, then open Ubuntu and run:
      sudo bash -c "$(curl -fsSL https://raw.githubusercontent.com/brevdev/brev-cli/main/bin/install-latest.sh)"

      # Verify installation
      brev --version
      ```
    </CodeGroup>

    <Callout intent="success">
      **Expected output:** You should see a version number printed, confirming the CLI is installed.
    </Callout>
  </Step>

  <Step title="Authenticate">
    Log in to your Brev account. This opens your browser for authentication.

    ```bash
    brev login
    ```

    After logging in, your credentials are stored in `~/.brev/`. This directory also contains your SSH keys for connecting to instances.

    <Callout intent="tip">
      **For headless environments:** Use `brev login --token` to authenticate with an API token instead of browser OAuth. Copy the command from the [CLI settings page](https://brev.nvidia.com/settings/cli).
    </Callout>
  </Step>

  <Step title="Create and Connect to Your Instance">
    {/* QUICKSTART_GPU: nebius.l40sx1.pcie */}

    Create a GPU instance and open a shell session:

    ```bash
    # Create a GPU instance with an NVIDIA L40S
    brev create my-instance --gpu "nebius.l40sx1.pcie"

    # Open a shell on your instancefrom one of the following platforms
    brev shell my-instance
    ```

    The `brev create` command provisions an instance with the specified GPU. This takes a few minutes while the instance starts. Once ready, `brev shell` opens a terminal session on the instance.

    <Callout intent="tip">
      You can also create instances in the [Brev Console](https://brev.nvidia.com). If you do, run `brev refresh` to sync them to your CLI, then `brev list` to see all your instances.
    </Callout>

    Refer to the [GPU Types catalog](/reference/gpu-types) for all available GPUs.
  </Step>
</Steps>

## Verify Your Setup

After connecting to your instance, verify the GPU is available:

```bash
nvidia-smi
```

<Callout intent="success">
  You can see a table showing your GPU name (NVIDIA L40S), driver version, and CUDA version. This confirms the GPU is accessible and drivers are configured correctly.
</Callout>

## What's Next?

<CardGroup cols={2}>
  <Card title="Connect VS Code" icon="code" href="/guides/development-tools/vscode-setup">
    Set up VS Code Remote SSH for a full IDE experience.
  </Card>

  <Card title="Run Jupyter" icon="file" href="/guides/development-tools/jupyter-notebooks">
    Access JupyterLab with GPU acceleration through port forwarding.
  </Card>

  <Card title="Understand Instances" icon="microchip" href="/concepts/gpu-instances">
    Learn about instance lifecycle, states, and data persistence.
  </Card>

  <Card title="Master the CLI" icon="terminal" href="/cli">
    Explore all CLI commands for managing your instances.
  </Card>
</CardGroup>