# DigitalOcean Gradient™ AI GPU Droplets

GPU Droplets have GPUs in a single or 8 GPU configuration. They also come with two different kinds of storage: a boot disk for persistent data and a scratch disk for non-persistent data. [Learn more about GPU Droplet plans and features](https://docs.digitalocean.com/products/droplets/details/features/index.html.md#gpu-droplets).

We provide AI/ML-ready images for GPU Droplets that have drivers and software from AMD and NVIDIA preinstalled, as well as preconfigured [1-Click Models powered by Hugging Face](https://docs.digitalocean.com/products/marketplace/1-click-models/index.html.md). You can also create GPU Droplets with existing Droplet images, but you need to manually install drivers and other software to use the GPUs.

[How to Create and Configure DigitalOcean Gradient™ AI GPU Droplets](https://docs.digitalocean.com/products/droplets/how-to/gpu/index.html.md): Create and configure GPU Droplets, which are powered by AMD or NVIDIA GPUs.

[Recommended GPU Setup](https://docs.digitalocean.com/products/droplets/getting-started/recommended-gpu-setup/index.html.md): Follow our recommended setup for drivers and software on GPU Droplets to use their GPUs.

[DigitalOcean Gradient™ AI 1-Click Models](https://docs.digitalocean.com/products/marketplace/1-click-models/index.html.md): 1-Click Models let you deploy third-party generative AI models on [DigitalOcean Gradient™ AI GPU Droplets](https://docs.digitalocean.com/products/droplets/how-to/gpu/index.html.md) with no additional setup or configuration.

[How to Use NVIDIA Container Tools and Miniconda with Gradient GPU Droplets](https://www.digitalocean.com/community/tutorials/how-to-use-nvidia-container-tools-with-gpu-droplets): Set up the NVIDIA container toolkit, run Docker for GPU workloads, and install Miniconda to manage Python environments on GPU Droplets.