Cloud Infrastructure & DevOps★ EDITOR'S PICK · BUY· read full review ↓

E2B

Secure sandboxed code execution for AI agents — Firecracker microVMs that boot in 150ms, used by Perplexity and Manus.

Professional
Pricing Tier
Easy
Learning Curve
hours
Implementation
small, medium, large
Best For
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Use when

AI agents that need to run untrusted code, code-interpreter features, data-analysis assistants, sandboxed plugin systems.

Avoid when

Long-running compute jobs (use Modal), pure code execution without AI context (use AWS Lambda directly).

What is E2B?

E2B provides secure, ephemeral compute environments for AI-generated code. Built on Firecracker (the AWS Lambda underlying tech), each sandbox boots in ~150ms and runs arbitrary code with full filesystem and network. Powers Perplexity's code interpreter, Manus AI agent runtimes, and many of the long-tail AI agent builders that need to "just run Python safely." Open-source SDK with paid hosted infrastructure.

Key features

150ms cold-start Firecracker microVMs
Python and Node SDKs
Persistent filesystem within session
Internet access (configurable)
Code interpreter template (matplotlib, pandas pre-installed)
Open-source self-host option

Integrations

OpenAIAnthropicLangChainLlamaIndex
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StackMatch EditorialVerdict: BuyUpdated Apr 30, 2026

Sandboxed code execution for AI — the right primitive at the right time

Editor's summary

E2B gives AI agents a secure sandbox to run code, install packages, and execute commands. It's how OpenAI's Code Interpreter pattern gets reimplemented across every AI agent product without security disasters.

E2B solves a problem that every agent team eventually hits: "the LLM wrote code, now what runs it safely?" The answer was rolling your own Firecracker VMs, dealing with sandbox escape edge cases, or accepting the security and operational nightmare of `eval` on a server. E2B abstracts all of that into an SDK call: spin up a sandbox, run code, get results back. The sandboxes are durable enough for multi-step agent workflows but ephemeral enough to throw away after.

The competition matters here. Vercel Sandbox (GA January 2026) is the obvious alternative for teams already on Vercel and may be enough for many use cases. Modal also offers similar primitives with a different abstraction. E2B's edge is being purpose-built for agents — the SDK ergonomics are tuned for "give an LLM a Python REPL" and that focus shows.

Buy E2B if you're building AI agents that execute code (data analysis copilots, AI engineers, research agents). Evaluate Vercel Sandbox if you're already a Vercel shop and your sandbox needs are simpler. Skip if your agent doesn't execute code — you don't need a sandbox you're not using.

Best for

AI agent products that execute code as part of their workflow — data analysis copilots, research agents, AI engineers.

Not for

Agents that only call APIs and don't execute arbitrary code; or Vercel-native teams who can use Vercel Sandbox.

Written by StackMatch Editorial. StackMatch editorial reviews are independent analyst commentary, not user reviews. We have no affiliate relationship with this tool. See user reviews below for community perspective.

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