Recommended Drivers and Software for GradientAI GPU Droplets
Validated on 18 Jun 2025 • Last edited on 8 Jul 2025
DigitalOcean Droplets are Linux-based virtual machines (VMs) that run on top of virtualized hardware. Each Droplet you create is a new server you can use, either standalone or as part of a larger, cloud-based infrastructure.
We strongly recommend creating GPU Droplets using our AI/ML-ready images, which have drivers and software preinstalled and configured to help you get started.
GPU Droplets also work with other Droplet images (stock Linux images, backups, snapshots, and so on) but you need to manually install drivers and other software to use your Droplet’s GPUs.
If you have additional software you want to use across multiple GPU Droplets, one option is to start with our AI/ML-ready image, install any additional software, and then take a snapshot of the Droplet. You can then use the snapshot as the base image to create additional GPU Droplets.
AI/ML-Ready Image for NVIDIA GPU Droplets
For GPU Droplets with NVIDIA GPUs, our AI/ML-ready image is based on Ubuntu 22.04 and includes:
nvidia-container-toolkit=1.71.0cuda-keyring_1.1-1cuda-drivers-535cuda-toolkit-12-1bzip2(8 GPU Droplets only)MLNX_OFED_LINUX-23.10-1.1.9.0-ubuntu22.04-x86_64(8 GPU Droplets only)nvidia-fabricmanager-535(8 GPU Droplets only)
You can choose this image when you create a GPU Droplet from the control panel or specify it by slug name when you create a GPU using the API or doctl. For all single GPU Droplets, use gpu-h100x8base (even for single GPU plans using GPUs other than H100s). For 8 GPU Droplets, use gpuh100x8-base.
For manual setup, on Debian-based systems like Ubuntu, you can install the CUDA drivers and toolkit as well as the NVIDIA Container Toolkit with APT. On 8 GPU Droplets, our image installs additional software that requires more configuration, as noted above. We recommend following NVIDIA’s installation documentation for Fabric Manager and NVIDIA’s documentation on Mellanox OFED.
AI/ML-Ready Image for AMD GPU Droplets
For GPU Droplets with AMD GPUs, our AI/ML-ready image is based on Ubuntu 24.04 and is configured following the ROCm quick start setup, including rocm version 6.4.0 and amdgpu-dkms version 6.12.12.
You can choose this image when you create a GPU Droplet from the control panel or specify it by slug name when you create a GPU using the API or doctl using the slug gpu-amd-base.