GPUs & AI/ML

Validated on 31 Jan 2025 • Last edited on 31 Jan 2025

Build, train, and deploy AI agents with GenAI Platform, or support your custom AI/ML use cases with GPU Droplets, Bare Metal GPUs, and more DigitalOcean GPU offerings.

Build AI agents on GPU-powered infrastructure using foundation models and resources such as knowledge bases and agent routes.
GPU Droplets are VMs with NVIDIA H100 GPUs in a single or 8 GPU configuration. We provide an AI/ML-ready image and 1-Click Models so you can get started without manual setup.
DigitalOcean Bare Metal GPUs are dedicated, single-tenant servers with 8 NVIDIA H100 GPUs that can operate standalone or in multi-node clusters.
Paperspace is a cloud-based machine learning platform that offers GPU-powered virtual machines and a Kubernetes-based container service.

DigitalOcean Bare Metal GPUs and GPU Droplets both provide GPU-based compute resources tailored to AI/ML workloads, but they’re each suited for different use cases.

Click to learn more about the difference between bare metal GPUs and GPU Droplets.
GPU Droplets Bare metal GPUs
Virtual machines. GPU Droplets have the convenience and ease of deployment that comes with managed infrastructure, but VM configuration is constrained by the hypervisor and shared OS layer. Physical servers. Bare metal GPUs are physical servers without virtualization, so you can set up advanced orchestration layers, containers, operating systems, and other deep configuration directly on the hardware.
Shared infrastructure. GPU Droplets share physical resources, so there may be minor resource fluctuations that don’t significantly impact tasks like fine-tuning and inferencing. Single tenant hardware. Bare metal GPUs are in isolated environments, which are best for use cases requiring full data isolation or highly consistent performance.
On-demand instances with per-hour billing. Pricing for GPU Droplets is flexible and low commitment, so GPU Droplets are best for variable usage or rapid scalability. Contract-based billing and provisioning. Pricing for bare metal GPUs is more cost effective, but meant for long-term use with intensive, prolonged workloads that need stable performance.

GPU Droplets are best for small- to medium-scale tasks, including:

  • Fine-tuning (adjusting models with specific data sets)
  • Inference (running predictions with high-speed responses for production applications)
  • Moderate data processing (lightweight analytics or video processing that benefit from GPU acceleration but don’t demand full hardware dedication)

Bare metal GPUs are best for advanced and custom workloads, including:

  • Model training at scale (training foundational models and handling large datasets with optimal performance)
  • Complex inference needs (running real-time inference for high-throughput applications)
  • Custom orchestration and HPC (like Kubernetes clusters, multi-node setups, or high-frequency trading)

Latest Updates

21 February 2025

7 February 2025

31 January 2025

For more information, see the full release notes.

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