GPU & Dedicated Servers

Compute power. On your terms.

Explore GPU capacity and dedicated server configurations built around your applications, data and operating requirements.

Two ways to get the compute you need

Start with the workload. Choose accelerated GPU resources billed around usage, or dedicated hardware allocated to you — with the configuration, environment and responsibilities agreed before deployment.

GPU as a Service

Accelerated resources for AI and media workloads. Start with the model or application, required GPU memory and expected usage. Assess configurations for inference, training, rendering and video processing, with hardware and availability confirmed in the proposal.

Dedicated Servers

Allocated hardware for sustained workloads and control. Define a server configuration around processor capacity, memory, storage and network needs. Agree the operating environment and management responsibilities before deployment.

Match the infrastructure to the workload

AI Training & Inference

Size resources around model requirements, data volume and concurrency.

Cinematic Rendering

Assess application compatibility, scene complexity and output requirements.

Video Processing

Plan compute around codecs, resolution, throughput and software support.

Enterprise Applications

Configure dedicated resources for application servers, databases and business services.

How it works

Select what matters to your workload

01
Workload
Describe the application and expected utilisation.
02
Compute
Define GPU memory, processor and RAM requirements.
03
Storage
Specify capacity, throughput and persistence needs.
04
Network
Establish bandwidth, data movement and connectivity.
05
Deployment
Confirm region, duration, access and support scope.

Infrastructure for different workloads

AI & Research

Accelerated resources for training, fine-tuning and inference.

Media & Rendering

GPU capacity for cinematic rendering and video processing.

Dedicated Hosting

Allocated servers for applications requiring fixed hardware.

Hybrid Compute

Combine GPU and CPU-only servers across one planned architecture.

Start with your requirements

Share your preferred GPU configuration, CPU and RAM, storage needs, bandwidth and region. Include software dependencies and expected usage so the configuration can be assessed accurately.

Frequently asked questions

Which GPU models are available?

The available inventory is confirmed at quotation. No specific model, quantity or delivery date is promised on this page.

Is GPU capacity billed hourly or monthly?

Commercial terms depend on the configuration, allocation and deployment duration. Request a proposal for the applicable billing model.

Will my software run on the selected server?

Compatibility must be checked against the operating system, drivers, accelerator support and software licensing requirements.

Are backups and server management included?

Backup, monitoring and management services must be explicitly included in the agreed scope.

Can GPU and CPU-only servers be combined?

Discuss the application architecture and networking so the resources can be planned together.

Find your compute configuration.

Tell us what you need to run, where it needs to run and how much capacity you expect to use.