How to create and manage a GPU Instance

Reviewed on September 17, 2025

Scaleway GPU Instances feature dedicated high-end Nvidia GPUs, making them optimal for tasks such as data processing, artificial intelligence, rendering, and video encoding.

Once you've created your GPU Instance, connecting to it via SSH allows you to use our pre-configured Docker images, providing instant access to a preinstalled environment with your preferred AI libraries and tools already set up.

Moreover, GPU Instances offer all the functionalities of our standard Instances, including flexible IPs, Security Groups, Private Networks, backups, and more.

When you have completed your calculations using the GPU Instance, deletion can be done through the Scaleway console, API, or our CLI tools.

Before you start

To complete the actions presented below, you must have:

A Scaleway account logged into the console
Owner status or IAM permissions allowing you to perform actions in the intended Organization
An SSH key added to your account

How to create a GPU Instance

Click CPU & GPU Instances in the Compute section of the side menu. The Instance dashboard displays.
Click Create Instance, then select Create GPU Instance. The Instance creation wizard displays.
Select an Instance range based on your usage. Instance offers vary in pricing, processing power, memory, storage, and bandwidth. Discover the best Instance type for your needs.
Tip
Click Instance view > List to view a list of all available Instances.
Choose an Instance configuration from the list and click the select icon. A pop-up displays.
Select the Availability Zone in which you want to deploy your Instance. Then click Configure Instance.
Complete the following steps:
- Name your Instance, or leave the randomly-generated name in place. Optionally, you can add tags to help you organize your Instance.
- Image: Pick an operating system image suitable for your GPU Instance. For example, select Ubuntu Noble GPU OS 13 (NVIDIA), which comes with preinstalled NVIDIA drivers and an NVIDIA Docker environment. You can customize your working environment using Docker with our provided Docker images or your own containers.
- Add volumes, which are storage spaces used by your Instances. A block volume with a default name and 5,000 IOPS is automatically provided for your system volume. You can customize this volume and attach up to 16 local and/or block type volumes as needed.
  Important
  
  Ensure that the volume containing your OS image has a minimum size of 10 GB. For a GPU OS, the recommended size is 125 GB.
  
  When multiple Block Storage volumes are linked to your Instance, the primary volume will host the OS and is essential for booting the Instance. If needed, you can change the boot volume after the Instance creation.
  
  Booting from a volume that either lacks an OS or is among multiple volumes with identical operating systems can lead to inconsistent boot outcomes.
- Configure network of the Instance.
  - Leave the checkbox ticked to assign a Public IPv4 to the Instance. You can either allocate a new IPv4 address or select one or multiple existing IPv4s. Alternatively, uncheck the box if you do not want an IPv4.
  - Leave the checkbox ticked to assign a Public IPv6 to the Instance. You can either allocate a new IPv6 address or select one or multiple existing IPv6s. Alternatively, uncheck the box if you do not want an IPv6.
    Note
    You can attach up to 5 IPv4 and 5 IPv6 addresses to an Instance, which is useful for running different services or applications on the same Instance.
- (Optional) Click Cloud-init to set up a cloud-init configuration. Otherwise, leave this option set to its default values. Cloud-init scripts are the standard way to automate Instance setup, such as setting up software, users, and system configurations at the first boot.
- Verify the SSH keys that will give you access to your Instance.
Click Review to see a order summary. Verify the estimated cost of your Instance, based on the specifications you chose.
Click Create Instance. The creation of your Instance begins, and you will be informed when the Instance is ready.

How to connect to a GPU Instance

See our documentation on how to connect to your Instance via SSH.

Once you have connected via SSH, you can launch a Docker container to start working on your AI projects.

How to use Instance features

For instructions on using any type of GPU Instance feature, including flexible IPs, placement groups, Private Networks, backups, and much more, check out our full Instance how-to documentation.

How to delete a GPU Instance

See our documentation on how to delete your Instance.