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GPU CloudAMD MI325X and NVIDIA H200 by the hour or on reservation.
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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Sandboxes

Preview

A fresh machine for every task, human or agent.

Start a sandbox from a template in seconds, run commands, edit files and open preview ports, then snapshot it or let it expire. Agents drive the same API with scoped keys, and every exec is authorized and audited.

Request accessView pricing
Pricing
Per vCPU, memory and disk hour
Layer
Compute
Drive it from
The console, The API, TypeScript client, MCP, Pipelines, Git, Datasets

Why Sandboxes

Short-lived by design, safe by default.

A sandbox is an isolated environment you start from a template, use and let expire. Developers work in it from the browser, agents drive it through the same API with scoped keys, and every command is authorized and audited.

  • Exec, files and git

    Run commands, stream logs and work with files from the console or the API.

  • Preview ports

    Share a running port behind a signed, expiring link.

  • Templates and snapshots

    Build once, start fresh copies, and save state when you need it.

How it works

Isolated, short-lived environments for developers and AI agents.

  1. Build a template

    Describe the image, the resources and the GPU types once. Build logs stream to the console while it builds.

  2. Start a sandbox

    Start a fresh copy from the template or from a snapshot, with a time to live and a network policy: no network, private, or open egress.

  3. Work in it

    Run commands in the terminal, stream logs, move files and clone repositories with git credentials taken from your secrets.

  4. Share, save or let it go

    Share a running port behind a signed, expiring link, snapshot the state you want to keep, or let the sandbox expire.

In the console

Everything in one place.

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

  • Sandbox page

    One sandbox, with a tab for each way you work with it.

    • Terminal, files, ports and previews
    • Logs, metrics and snapshots
    • Extend the time to live from settings

  • Templates

    Build an environment once and start as many fresh copies as you need.

    • Image, resources and GPU types in fallback order
    • Streaming build logs
    • Volumes, with dataset versions mounted read-only

  • Agent access

    Agents use sandboxes the way people do, with exactly the access you give them.

    • API keys scoped to sandbox actions
    • A TypeScript client and an MCP endpoint
    • A pipeline step that always cleans up its sandbox

  • Audit and access

    Every action is checked against IAM before it runs.

    • Every exec authorized and audited with a command hash
    • Agent calls recorded as agent actions
    • Preview viewers authorized before they reach a port

Pricing

Per vCPU, memory and disk hour

Sandboxes are metered on the vCPU, memory and disk they reserve, for as long as they hold them, with GPU time metered separately when a template asks for one.

Full pricing
  • Stopped or paused sandboxes pay for disk only.
  • Archived sandboxes pay nothing.
  • Your organization sets the longest a sandbox may live, so nothing runs forgotten.

Related products

Pairs well with Sandboxes

Get started

Start with a workload.

Connect to the platform directly, or work with our team on a specific technical challenge.

Self-service

LegionEdge Cloud

Create a workspace, explore the available models, and connect your application. The documentation takes you through your first request.

  • Turn on only the services you need
  • Pay per token or per GPU-hour
  • One account, one bill
Create a workspaceRead the docs

Custom engagements

Work with our team

Bring your data requirements, model goals, or infrastructure constraints. We'll define the scope, deliverables, and next steps together.

  • Scoped with an evaluation baseline
  • Dedicated clusters and reserved GPUs
  • A named engineer from day one
Discuss your projectsales@legionedge.ai