DigitalOcean Gradient™ AI Agentic Cloud

Build, train, and deploy AI agents with the DigitalOcean Gradient™ AI Agentic Cloud:

DigitalOcean Gradient™ AI Platform

Build AI agents on GPU-powered infrastructure using foundation models and resources such as knowledge bases and agent routes.

DigitalOcean Gradient™ AI GPU Droplets

GPU Droplets are VMs with 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 Gradient™ AI Bare Metal GPUs

DigitalOcean Gradient™ AI Bare Metal GPUs are dedicated, single-tenant servers with eight GPUs per machine. They can run as standalone servers or as part of multi-node clusters.

DigitalOcean Gradient™ AI 1-Click Models

1-Click Models let you deploy third-party generative AI models on DigitalOcean Gradient™ AI GPU Droplets with no additional setup or configuration.

Paperspace

Paperspace is a cloud-based machine learning platform that offers GPU-powered virtual machines and a Kubernetes-based container service.

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. Learn more about the difference between bare metal GPUs and GPU Droplets.

Latest Updates

27 March 2026

• The following OpenAI models are now available on DigitalOcean Gradient™ AI Platform for serverless inference and Agent Development Kit:

  • GPT-5.4 mini
  • GPT-5.4 nano
  • GPT-5.4 pro
  • GPT Image 1.5

  For more information, see the Available Models page.

17 March 2026

• The following NVIDIA model is now available on DigitalOcean Gradient™ AI Platform for serverless inference, Agent Development Kit, and agents:

  • Nemotron-3-Super-120B (Public Preview)

  For more information, see the Available Models page.

16 March 2026

• Gradient AI Dedicated Inference Service is a managed LLM hosting service for optimized inference on dedicated GPUs, now available in public preview and enabled for all users. For more information, see Use Dedicated Inference.

For more information, see the full release notes.