E2B by FoundryLabs, Inc.

E2B is an open-source platform for running AI-generated code in secure, isolated cloud sandboxes. It uses Firecracker microVMs to create sandboxes that start in about 150 milliseconds, supporting Python and JavaScript/TypeScript SDKs. Developers can execute code from any LLM, manage sandbox filesystems, and customize environments with specific CPU and RAM configurations. E2B supports up to 24-hour sandbox sessions and up to 100 concurrent sandboxes on the Pro Tier.

The platform’s Code Interpreter SDK simplifies adding code execution to AI apps, such as coding copilots or data analysis tools. Users can upload and download files, install packages, and pause sandboxes for data persistence. E2B is LLM-agnostic, compatible with models like OpenAI or Anthropic. The Hobby Plan offers $100 in free credits, while the Pro Tier supports longer sessions and more concurrent sandboxes. The open-source infrastructure allows self-hosting on AWS or GCP.

Developers may appreciate the secure isolation and fast startup times. The SDKs are well-documented, and the community on X provides active support. Use cases include AI-driven data visualization, codegen evaluations, and app generation, as seen in projects like Maige for GitHub issue automation.

Drawbacks include a learning curve for beginners, as SDK setup and sandbox management require some technical knowledge. Language support is limited to Python and JavaScript/TypeScript. Some users report slowdowns with complex workloads, like Next.js apps, taking 30-40 seconds to render. Compared to CodeSandbox, which supports broader web development, or Replit, which offers a more user-friendly interface, E2B is more specialized for AI use cases.

For best results, follow the Quickstart guide on E2B’s website to set up the SDK. Test with simple scripts before scaling to complex projects. Use the cookbook on GitHub for LLM-specific examples, and monitor the changelog for performance improvements.