Dedicated server resources — Ashburn, Virginia
Match CPU, memory and storage to your application. Final specifications will be listed with each plan.
Infrastructure for your workload
Rent Dedicated GPU Servers in the USA
GPU servers in the USA offer maximum performance and minimal latency for AI-driven, global, and US-focused projects. They are perfect for machine learning, deep learning, 3D rendering, and video processing. Hosted in Tier III certified data center and equipped with modern GPUs such as A-Series, they ensure top-tier reliability and compute power.
Configuration catalogue in preparationPlans will be available later
Explore the service and choose a location. Available configurations, prices and ordering terms will be published with the plans.
GPU servers
What to consider before choosing
Location near your users
Consider your audience, connections to other services and data location requirements.
Operating requirements
Check available operating systems, server management, backups and support terms before ordering.
Our US-based GPU servers deliver the compute power needed for demanding analytics, neural network training, visualization, and parallel workloads. You'll benefit from full root access, scalable configurations, and dedicated hardware tailored to your project. You choose:
- GPU model and number of graphics cards per server
- CPU architecture, RAM volume, and storage options
- Preferred US location and bandwidth capacity.
Advantages of Renting a GPU Server in the USA
A dedicated GPU server in the USA offers:
- High-speed and fault-tolerant infrastructure
- Unrestricted access to high-end GPU computing
- Full support for AI/ML stacks and software environments
- Peak performance with global reach and low-latency access.
Before you order
When will plans be available?
Configurations and prices are being prepared. They will appear on this page when the catalogue is published.
Can I order a server now?
Ordering is not yet available on this page. Terms and ordering links will be published together with the plans.
How should I choose a configuration?
Start with your application requirements: CPU or GPU, memory, storage workload and user location. Then compare them with the published configurations.