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GPU CloudNVIDIA H200 by the hour.
Dedicated ClustersPreviewPrivate, interconnected GPU clusters for sustained workloads.
SandboxesPreviewIsolated, short-lived environments for developers and AI agents.
Serverless GPUPreviewGPU containers that scale with requests, down to zero.
Serverless InferenceOpen models behind one OpenAI-compatible endpoint.
Dedicated EndpointsReserved serving capacity for one model, billed per GPU-hour.
PlaygroundSend a prompt to any model your workspace can reach.
Model DeploymentsPreviewImmutable deployments with instant promote and rollback.
Fine-tuningLoRA fine-tunes on the open models in our catalog.
Model TrainingPreviewFoundation-model training runs, managed end to end.
EvaluationsPreviewBenchmark suites and model comparisons you can rerun.
DatasetsManaged and synthetic training data, versioned and ready to use.
Data ManagementPreviewDatasets, connections and storage, with lineage across the platform.
PipelinesPreviewVersioned DAGs that automate data, training and deployment.
Data RoomsPreviewSecure document sharing with guests, NDAs and an audit trail.
NokuvaPreviewThe AI-native design editor.
TavocPreviewA Rust-native code platform: IDE and desktop apps.
FoltracComing soonMulti-cloud deployment with autonomous operations.
W0rkTreeComing soonVersion control for agent fleets.
Identity & AccessMembers, roles, policies, SSO and audit for every workspace.
Billing & CostUsage, invoices, credits and budgets in one place.
Logs & MonitoringRequest logs, latency and error rates across services.
Project CanvasPreviewSee and change a project's resources on one live canvas.

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GPU Cloud

Available

The fleet behind our research, by the hour.

Launch GPU capacity in minutes and pay for the hours you use. The same fleet serves our own inference and training.

Request accessView pricing
Pricing
$4.79 / GPU-hr
Layer
Compute
Launch with
NVIDIA H200, CUDA images, PyTorch, vLLM, SSH keys, Project canvas

Why GPU Cloud

One console for every GPU you run.

Pick an offer by GPU, region, price and availability, launch it from the console or stage it on your project canvas, and follow utilization, memory and power for each GPU while it runs. The same fleet serves our own inference and training.

  • On demand

    H200 141 GB at $4.79 per GPU-hour.

  • Live telemetry

    Utilization, memory and power for every GPU you run.

How it works

NVIDIA H200 by the hour.

  1. Pick the hardware

    The launch wizard lists offers by GPU, region, price and availability, with the hourly rate in front of you before anything starts.

  2. Configure the instance

    Choose an image from the curated CUDA, PyTorch and vLLM builds, add SSH keys and disk, and pick the project and environment it belongs to.

  3. Launch or stage

    Launch it straight away, or stage it on the project canvas and deploy it with the rest of a changeset.

  4. Run and watch

    Open the instance for its metrics, logs and SSH, and power it off, reinstall, rescue or delete it from the same page.

In the console

Everything in one place.

GPU Cloud lives in the LegionEdge cloud console, next to every other service in the workspace, under one account and one identity.

  • Compute overview

    What is running across the organization, with quotas and budget status beside it.

    • Running instances and GPU-hours this month
    • Compute quotas next to IAM and API limits
    • A budget banner before you reach a limit

  • Instance detail

    Everything about one instance, from first boot to deletion.

    • Utilization, memory and power for every GPU
    • Serial console output and logs
    • SSH, power, reinstall, rescue and delete

  • Images and access

    A ready environment on first boot, reachable only with the keys you name.

    • Curated CUDA, PyTorch and vLLM images
    • SSH keys from the workspace key store
    • Boot disk sized at launch

  • Guardrails

    Spend limits and permissions the platform enforces on every launch.

    • Budgets that stop new launches, or drain running ones
    • A disabled Launch button that says why
    • Every launch authorized as a compute action in IAM

Pricing

$4.79 / GPU-hr

Capacity is metered by the GPU-hour on demand, with no instance minimums and no term to commit to.

  • Hard budget caps you set yourself: nothing scales past a limit you didn’t write down.
  • The launch wizard checks your budget before an instance starts.
  • On-demand billing meters exactly the hours you use.
Full pricing

GPU rates

GPU rates in USD per GPU-hour, on demand
GPUMemoryOn demand
NVIDIA H200141 GB HBM3e$4.79

Regions

Compute regions
RegionLocationHardwareStatus
US Southus-south-1Dallas, TXNVIDIA H200Live
US Eastus-east-1Ashburn, VANVIDIA H200Planned

Related products

Pairs well with GPU Cloud

GPU Cloud

Launch in minutes. Pay for the hours you run.

The same console, images and telemetry that run our own inference and training.

Request accessTalk to us