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E2B

Secure cloud sandboxes for AI agents

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E2B provides secure cloud sandboxes that let AI agents execute code, run terminal commands, and interact with filesystems in isolated environments. Each sandbox spins up in ~150ms with its own OS, giving agents a safe space to run untrusted code. Supports Python, JavaScript, and any language via custom Dockerfiles. Used by AI coding assistants, data analysis agents, and code interpreters. SDK available for Python and JavaScript with a simple API for programmatic sandbox control.

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E2B provides cloud-based sandboxed environments specifically designed for AI agents and LLM applications. Each sandbox is a lightweight micro-VM with its own isolated OS that starts in approximately 150 milliseconds, giving AI agents a secure space to execute code and interact with filesystems.

The platform solves a critical challenge in agentic AI: allowing AI agents to execute arbitrary code safely. Agents can run Python scripts, install packages, execute terminal commands, read and write files, and even run web servers — all within an isolated environment that cannot affect the host system.

Custom sandbox templates built from Dockerfiles enable pre-configuring environments with specific tools, libraries, and configurations. The SDK provides programmatic control over sandboxes through Python and JavaScript/TypeScript, with simple APIs for code execution, file operations, and process management.

E2B is used as the code execution backend for AI coding assistants, data analysis agents, code interpreters, computer-use agents, and automated testing pipelines. Public pricing currently starts with a free Hobby tier that includes one-time usage credits, then Pro at $150/month plus usage and custom Enterprise/BYOC options.

Pricing

Hobby free with one-time $100 usage credits + usage costs. Pro $150/mo + usage. Enterprise/BYOC custom.

Platforms

API, Python SDK, JS/TS SDK, Docker

Categories

Agent FrameworksAgent Skills & Prompts

Tags

Open SourcePythonTypeScriptDockerAgentic

Use Cases

Agentic DevelopmentCode Generation

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Comparisons

Freestyle vs E2B — Agent-Native VM Stack or Mature Code Execution

Freestyle and E2B both promise secure sandboxes for AI coding agents, but they make different bets about what that sandbox should contain. E2B is the mature, container-based runtime trusted across the agent ecosystem — LangChain, LlamaIndex, OpenAI cookbooks — while Freestyle is the newer, heavier stack that bundles Linux VMs, Git, deploys, and execution as one trust boundary.

FreestyleE2B

E2B vs Daytona — Ephemeral Code Sandboxes vs Stateful Development Environments for AI

E2B and Daytona provide isolated environments for AI code execution with different persistence models. E2B offers ephemeral Firecracker microVM sandboxes destroyed after use for clean-slate execution. Daytona provides stateful Docker-based workspaces that persist across sessions, treating each environment as a long-lived development workspace rather than a disposable execution unit.

E2BDaytona

E2B vs Microsandbox — Cloud Firecracker Sandboxes vs Self-Hosted Container Isolation

E2B and Microsandbox both provide isolated environments for AI-generated code but with different deployment models. E2B offers managed Firecracker microVM sandboxes in the cloud with sub-200ms startup and Fortune 500 adoption. Microsandbox provides self-hosted lightweight container sandboxes that run on your own infrastructure with lower latency and no per-execution cloud costs.

E2BMicrosandbox

Lume vs E2B — macOS VM Runtime vs Cloud Sandbox Platform

Lume and E2B both provide isolated environments for running AI agents safely, but their architectures serve different deployment models. Lume creates native macOS and Linux VMs on Apple Silicon for local agent sandboxing, while E2B offers cloud-hosted micro-VMs optimized for code execution. The choice depends on whether you need local Apple Silicon isolation or scalable cloud sandboxes.

LumeE2B