Explore the full DigitalOcean AI-Native Cloud, from GPUs and silicon to inference, data, and agents, with economics that improve as you scale.
Production agents that run on the same stack as your data, inference, and infrastructure. No cross-vendor hops. No lost context. No egress fees between layers.
Fresh data, persistent memory, and continuous learning, without rebuilding your data stack.
Over 70 models, open-weighted and frontier, on one endpoint. Run serverless, dedicated, or batch inference, with the Inference Router optimizing every call.
Sometimes we need to scale up, but hyperscalers don't have any GPUs left. The low-cost local data centers have fragile reliability and stability. We were looking for a provider like DigitalOcean that sat between these two options, which had availability but also reliability at scale.
Sean Zhao
ACE Studio, Co-Founder
Go from idea to a production-ready application in as little as minutes with fully configured starter kits for RAG assistants, data pipelines, and observability. No infrastructure expertise required.
A serverless computing solution that runs on-demand, enabling you to focus on your code, scale instantly with confidence, and save costs by eliminating the need to maintain servers.
Worry-free database hosting. Leave the complexity of database administration to us. We'll handle setting up, backing up with Point-in-Time Recovery (PITR), and updating so you can focus on building great apps.
Fully managed Retrieval-Augmented Generation (RAG) service that enables developers to build, test, and deploy AI-powered search and Q&A applications without managing embedding infrastructure, vector databases, or retrieval logic.
Production-ready vector infrastructure for AI apps with 1-click provisioning and predictable pricing, starting at just $20/month.
Policy-driven control replaces manual routing logic and adapts in real time. Teams define routing behavior using natural language or structured rules to optimize for cost, latency, and reliability without hardcoding models.
Structured testing enables validation of catalog, Bring Your Own Model (BYOM), and inference routers using real datasets before production deployment. LLM-as-a-judge evaluates quality, latency, cost, and safety, with a unified dashboard to compare results and re-run evaluations as models evolve.
A unified playground enables experimentation across text, image, audio, and video models in a single interface. Side-by-side testing, real-time inference, and exportable production-ready API code support rapid transition from experimentation to implementation.
Controlled, high-performance model hosting supports sustained production workloads with dedicated infrastructure. Dedicated GPU endpoints, BYOM support, and configurable scaling and performance settings enable production-grade control without Kubernetes complexity.
Real-time AI inference supports applications, APIs, and agents through a unified system. The platform provides access to 70+ models with multimodal generation, intelligent routing for cost and latency optimization, and built-in observability for production workloads.
Large-scale asynchronous workloads run through job-based inference designed for non-real-time use cases. Batch processing includes up to 50% cost savings and support for evaluation, enrichment, and moderation pipelines.
Deploy popular AI models from providers like Hugging Face and DeepSeek on GPU Droplets with just a single click.
Always-on input and output content evaluation built into every inference request, applying policy-based allow/flag/block decisions to help support compliance needs with AI-generated content.
A single pane of glass across every model on the platform with side-by-side evaluation, benchmark comparison, and one-click deployment, with day-zero availability of select new models as they ship.
On-demand Linux virtual machines. Choose from shared CPU and dedicated CPU plans, with variable amounts of RAM, locally attached SSD storage, and generous transfer quotas.
Simple, affordable, and flexible virtual GPUs from NVIDIA and AMD, designed to reliably run training and inference on AI/ML workloads and to process large datasets and complex neural networks.
Support complex and custom AI/ML use cases for your most demanding workloads.
Build, deploy, and scale apps quickly using a simple, fully managed solution. We'll handle the infrastructure, app runtimes and dependencies, so you can focus on your code.
An easy-to-use managed Kubernetes service for both GPU and CPU workloads, providing you uptime, scalability, and portability for your cloud native apps. Free control plane included.
Secure, isolate, and scale application traffic with built-in networking primitives including VPCs, load balancing, firewalls, Private IP and hybrid connectivity.
Store and access any amount of data reliably in the cloud, with S3-compatible Spaces Object Storage, network-based Volumes block storage, or NFS-based Network File Storage.
Create and manage compute environments with flexible images, including prebuilt distributions, 1-Click apps, snapshots, backups, and custom images.
Protect infrastructure with identity controls, posture management, and built-in DDoS protection to keep cloud environments secure and resilient.
Protect your Droplet data with automated daily* backups and Augment your data backups with on-demand images of Droplets.
Deliver applications globally with a resilient, distributed infrastructure spanning 18 data centers across 5 global regions.
Have a complex setup or additional questions around pricing? Contact our sales team to get more information on DigitalOcean pricing.

From GPU-powered inference and Kubernetes to managed databases and storage, get everything you need to build, scale, and deploy intelligent applications.
