GPU Service (coming soon)

GPU Service

GPU compute across three delivery models: instances, bare-metal servers, and dedicated clusters.

GPU Service is not yet generally available. Reach out to sales to discuss your workload and request priority access.

Typical workloads

Dedicated GPU resources with full control

01

Deploy your own models and lightweight apps

Flexible GPU environments for specialized model deployments and lightweight services.

02

Elastic compute scaling

Elastic scheduling for bursty, task-driven GPU workloads.

03

Diverse runtime environments

Hybrid environments for running agent, RAG, and multimodal inference workloads side by side.

04

Rapid prototyping

On-demand capacity for short-cycle experiments, with elastic billing.

Delivery models

One platform, three ways to deploy

Instance

GPU Instance

On-demand single- or multi-GPU instance containers — provisioned in minutes, billed by the hour.

Bare-metal

Bare-Metal

Dedicated GPU servers with full hardware control and resource isolation.

Cluster

Cluster

A multi-node networked compute pool sized for large-scale inference.

Get started

Tell us what you want to run.

Share your workload and requirements, and our team will follow up with a deployment plan.