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Lightning AI Sandbox

Answer in brief

Isolated, programmatic Linux sandboxes on the Lightning AI platform with Python and TypeScript SDKs, a CLI, filesystem snapshots and optional Docker-in-sandbox. A capable SDK-driven sandbox for Lightning AI users, held back by undocumented isolation and the absence of a dedicated rate card.

By the Agent Sandboxes editors · Updated November 9, 2026

Overview

Lightning AI Sandbox is the sandbox product of Lightning AI's cloud platform (the company behind PyTorch Lightning). The docs describe it as giving "every workload its own isolated Linux environment, spun up in milliseconds and torn down when you're done", aimed at running LLM-generated code, agent output, repository tests and live preview servers. You create sandboxes from the lightning-sdk Python package, the @lightningai/sdk TypeScript package or the lightning sandbox CLI, with runtimes node24 (default), node22, python313 or your own OCI image, always with sudo. A --docker flag provisions a Docker-enabled sandbox and --spot places it on spot capacity.

Sandboxes can be ephemeral or persistent; persistent ones stop and resume with their state auto-saved, and filesystem snapshots can be captured with an expiry and restored into new sandboxes. Five CPU shapes run from 1 vCPU/1 GB to 16 vCPU/64 GB; there are no GPU shapes for Sandbox. The isolation technology is not named in the docs. Lightning publishes no Sandbox-specific rate card — usage draws on the platform's per-second credit billing (Free, Pro $50/month, Teams $140/user/month). The company holds SOC 2 Type II and offers private deployments in the customer's AWS or GCP account.

Notable

Docs claim sandboxes "start in milliseconds"; the CLI supports --spot placement and a --docker mode that starts a Docker daemon at boot.
Platform pricing page: Pro $50/month, Teams $140/user/month; up to 30 free credits to start.
Lightning states SOC 2 Type II compliance covering AWS and GCP in all regions; HIPAA is tied to Enterprise and private deployments.

Lightning AI Sandbox specifications

Attribute	Details
Isolation	Not named; docs say each sandbox runs in a "strongly isolated environment, keeping its filesystem, network, and processes separate" with "dedicated compute" and its own network stack
Deployment	Hosted platform · BYOC available
Open source	No
SDKs and interfaces	Python, JavaScript/TypeScript, CLI
Cold start (vendor claim)	Docs claim "Sandboxes start in milliseconds"
Max session length	Configurable per sandbox (`--timeout` in milliseconds auto-stops it); no default or maximum published
Persistence	Persistent sandboxes "auto-save state on stop and resume right where you left off" (stop/start/resume); ephemeral mode available; filesystem snapshots (not running processes) can be created, listed, given a TTL and restored into a new sandbox
GPU	No — documented instance types are CPU only (cpu-1 1 vCPU/1 GB to cpu-16 16 vCPU/64 GB); the wider Lightning platform sells GPUs but not for Sandbox
Networking	Expose ports with `--port` and get a live preview URL for dev servers; internet access and allow-listing are not described
Pricing	No Sandbox-specific rates published. Platform plans: Free $0 (up to 30 starter credits), Pro $50/month (40 credits/month), Teams $140/user/month (50 credits/month), Enterprise custom; usage is billed by the second in credits
Free tier	Free plan with 5 credits on registration and 25 more on adding a card; Sandbox allowance not stated separately
Compliance	SOC 2 Type II ("with support for AWS and GCP Clouds in all regions"); HIPAA listed for Enterprise and private deployments
Regions	Not documented

Facts from Lightning AI Sandbox’s public documentation, verified November 9, 2026. Performance numbers are vendor claims.

Strengths and trade-offs

Strengths

You want Python and TypeScript SDKs plus a CLI with persistent or ephemeral sandboxes on one platform
You need Docker inside the sandbox or spot pricing for cheap batch runs
You are already using Lightning Studios or GPU jobs and want sandboxes in the same teamspace

Trade-offs

Isolation technology is not documented (no VM, microVM or container claim)
No Sandbox-specific pricing, no GPU instance types, no stated session limits or regions
Networking controls (egress allow-listing) are not described

Good fit for: Teams already on Lightning AI who want agent sandboxes next to their Studios and GPU jobs.

How Lightning AI Sandbox compares

Sandbox	Isolation	Open source	Self-host / BYOC	Cold start (vendor)	Max session	Snapshots / pause	GPU	SDKs
Lightning AI Sandbox	Not named (isolated Linux env)	No	No / Yes	ms (claimed)	Not documented	Yes / Yes	No	Python, JavaScript/TypeScript, CLI
Modal Sandboxes	gVisor or VM	No	No / Not documented	<1 s	Up to 24 h	Yes / Yes	Yes	Python, JavaScript/TypeScript, Go
E2B	Firecracker microVM	Yes	Yes / Yes	Not documented	1 h / 24 h (Pro)	Yes / Yes	No	Python, JavaScript/TypeScript
Daytona	Containers or VMs	No	Not documented / Yes	<90 ms	Unlimited	Yes / Yes	Yes	Python, TypeScript, Ruby, Go, Java
Baseten Sandboxes	Not named (Blaxel-based)	No	No / No	Not documented	7 days default	No / Yes	Not documented	Python, JavaScript/TypeScript, Go, CLI, REST API, MCP server
Prime Sandboxes	microVM, own kernel	No	No / No	Not documented	60 min default, unlimited	Yes / Yes	No	Python, CLI, REST API
Beam Sandboxes	gVisor	Yes	Yes / Yes	~0.5 s	Configurable	Yes / Yes	Yes	Python, TypeScript

See all Lightning AI Sandbox alternatives →

Frequently asked questions

What is Lightning AI Sandbox?

How does Lightning AI Sandbox isolate code?

Lightning AI Sandbox documents its isolation as: Not named; docs say each sandbox runs in a "strongly isolated environment, keeping its filesystem, network, and processes separate" with "dedicated compute" and its own network stack.

Is Lightning AI Sandbox open source?

No, Lightning AI Sandbox is not open source. It does offer a bring-your-own-cloud deployment.

How much does Lightning AI Sandbox cost?

No Sandbox-specific rates published. Platform plans: Free $0 (up to 30 starter credits), Pro $50/month (40 credits/month), Teams $140/user/month (50 credits/month), Enterprise custom; usage is billed by the second in credits Check the official pricing page for current rates.

What are the alternatives to Lightning AI Sandbox?

Common alternatives include Modal Sandboxes, E2B, Daytona, Baseten Sandboxes, Prime Sandboxes, Beam Sandboxes. See Lightning AI Sandbox alternatives for a full comparison.

Sources

Cite this page

Agent Sandboxes. (2026). Lightning AI Sandbox. agentsandboxes.org. Last reviewed November 9, 2026. https://agentsandboxes.org/sandboxes/lightning-ai-sandboxes/

Found an error or a missing sandbox? Submit a correction — every entry links to the sources it relies on.