> For the complete documentation index, see [llms.txt](https://docs.roboflow.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.roboflow.com/deployment/self-hosted/inference-server/install/cloud/gcp.md).

# Deploy on Google Cloud Platform

You can run Roboflow Inference on machines hosted on Google Cloud Platform (GCP). This is a good fit when you want the features of Inference while managing your own cloud infrastructure.

## Set up a Google Cloud compute VM

To get started you need a compute instance running on GCP. For provisioning instances we recommend SkyPilot, a tool designed to help you set up cloud instances for AI projects.

Run the following command on your own machine:

```bash
pip install inference "skypilot[gcp]"
```

Follow the [SkyPilot cloud account setup documentation](https://docs.skypilot.co/en/latest/getting-started/installation.html#cloud-account-setup) to authenticate with GCP, then run:

```bash
inference cloud deploy --provider gcp --compute-type gpu
```

This provisions a GPU-capable instance in GCP with the latest version of Roboflow Inference installed automatically.

When the command finishes you should see a message like:

```
Deployed Roboflow Inference to gcp on gpu, deployment name is ...
To get a list of your deployments: inference cloud status
To delete your deployment: inference cloud undeploy ...
To ssh into the deployed server: ssh ...
The Roboflow Inference Server is running at http://34.66.116.66:9001
```

You can then use that endpoint to run models: object detection, segmentation, classification, and keypoint models from your Roboflow workspace, plus foundation models like CLIP, PaliGemma, and SAM2.

## Next steps

Point your client at the new server by setting `api_url` to the IP address of your VM and the port the server is running on (`9001` by default). See [Run a model](/deployment/self-hosted/self-hosted.md#run-a-model) for the first request, and the [Inference CLI cloud commands](https://docs.roboflow.com/reference/inference/inference-cli/cloud) for managing deployments.

Before you expose the server beyond a private network, review [Securing a Self-Hosted Server](/deployment/self-hosted/inference-server/configuration/security.md).