Power your AI workloads with high-performance GPU hosting
Deploy, train, and scale your AI models faster with cost-efficient GPU infrastructure on DigitalOcean. Tap into high-performance GPUs to power demanding workloads, from large language models (LLM) training to real-time inference, without the overhead of managing complex infrastructure.
Build faster, launch smarter, with less overhead
Whether you’re a solo builder, a startup team, or an AI lead scaling production workloads, DigitalOcean’s GPU hosting makes it easy to get started. Skip the headaches of driver installs, compatibility issues, and setup scripts. DigitalOcean’s AI GPU hosting comes with pre-configured environments, simple APIs, and integrated ML frameworks.
Deploy scalable GPU hosting for training, inference, and more
Take full control of your model training and inference with GPU Droplets optimized for deep learning, generative AI, and high-performance computing (HPC).
Choose the right GPU for your workload
Select from a range of NVIDIA and AMD GPUs, including H100, L40S, RTX 6000 Ada, RTX 4000 Ada, AMD MI300X, and MI325X, to match your compute needs, from fine-tuning LLMs to running real-time inference at scale.
Scale with Multi-GPU support
Spin up multi-GPU Droplets and distribute compute-intensive tasks across GPUs for faster training and increased throughput, no complex setup required.
Scale smarter, spend less on AI GPU hosting
Optimize your AI infrastructure without overspending. DigitalOcean GPU Droplets offer the flexibility to scale vertically or horizontally based on your workload. Enjoy predictable pricing and save up to *75% compared to leading hyperscalers, all while powering your AI projects with enterprise-grade NVIDIA or AMD GPUs.
*Up to 75% cheaper than AWS for on-demand H100s and H200s with 8 GPUs each. As of April 2025.
Integrate with your ML stack
Easily connect your preferred tools, like PyTorch, TensorFlow, Hugging Face, and more, with pre-installed drivers and ML libraries that get you started faster.
The simpler way to power serious AI
Whether you're building gaming, chatbots, vision systems, recommendation engines, or deploying real-time AI agents, GradientAI GPU Droplets deliver scalable compute without the overhead of complex infrastructure. Choose from top-tier NVIDIA and AMD GPUs, launch in minutes, and only pay for what you use.
Train LLMs and fine-tune models
High-memory GPUs like H100 and MI300X help you train and fine-tune LLMs.
Achieve faster results and avoid memory bottlenecks.
Generate high-quality content
Use RTX Ada GPUs for media generation / 3D modeling and video rendering.
They are well-suited for creative workflows with high performance demands.
Run inference at scale
Deploy production-ready inference pipelines using serverless or multi-GPU Droplets.
Perfect for real-time AI experiences in applications like virtual assistants / image recognition and automation.
Analyze big data fast
Power your analytics - data science and HPC workloads with high-throughput compute and memory-optimized configurations.
NVIDIA H100 / H100x8 – Up to 4× faster training over A100
AMD MI325X/ MI325Xx8/ MI300X / MI300Xx8 – High bandwidth for massive models
NVIDIA RTX 4000 & 6000 Ada and L40S – For graphics / media and AI inference
Coming Soon: NVIDIA H200 – Double the memory of H100; ready for next-gen AI.
Resources to help you build
Explore faster training and parallel processing with the power of multi-GPU infrastructure.
Discover how GPUs accelerate AI, gaming, and scientific computing with parallel processing.
Performance isn’t just about cores; GPU memory hierarchy can make or break your workload.
Not all GPUs are created equal—choose the right one for your AI, rendering, or analytics needs.
FAQs
What is AI GPU hosting?
AI GPU hosting provides cloud-based access to powerful Graphics Processing Units (GPUs) optimized for training and running machine learning and deep learning models. It eliminates the need for expensive on-premise hardware, allowing teams to scale compute resources on demand.
Who should use AI GPU hosting?
AI GPU hosting works for developers, data scientists, researchers, and startups training and deploying LLMs, computer vision models, generative AI solutions, or real-time inference systems.
Which frameworks are supported?
Most AI GPU hosting platforms, like DigitalOcean, support popular frameworks such as PyTorch, TensorFlow, JAX, and Hugging Face transformers, with pre-installed drivers and dependencies for faster setup.
Can you run AI on a GPU?
Yes, GPUs are specifically designed to accelerate the parallel computations used in AI and deep learning, making them faster than CPUs for training and inference.
What GPU is recommended for AI?
The best GPU depends on your workload. For training large models, AMD MI300X and MI325X are strong options. For fine-tuning, NVIDIA L40S or RTX 6000 Ada provides an excellent balance of cost and performance. For inferencing, we recommend NVIDIA RTX 4000 Ada, 6000 Ada, or L40S.
Sign up for the GenAI Platform today
Get started with building your own custom AI HR knowledge assistant on the GenAI platform today.
