E2BSecure cloud sandboxes for running AI-generated code and autonomous agents
Overview
Key features
- Isolated cloud sandbox environments
- SDKs for Python and JavaScript
- Custom environment templates
- File system and process access
- Long-running session support
- Designed for AI agents and code interpreters
Pricing
- Model
- Free
- Category
- Model Serving
- Rating
- 4.5 / 5 (4)
Use cases
Run LLM-generated code safely
Execute code produced by large language models inside isolated cloud sandboxes, protecting host systems from untrusted or experimental output.
Power autonomous AI agents
Give agentic applications a secure runtime with file system and process access, enabling them to perform multi-step tasks over long-running sessions.
Build a code interpreter feature
Integrate E2B via the Python or JavaScript SDK to add a ChatGPT-style code interpreter to your product for data analysis and computation.
Preconfigured dev environments
Use custom templates to spin up sandboxes with specific dependencies and tooling, standardizing runtimes across AI-powered developer tools.
Pros & Cons
Pros
- Strong isolation for running untrusted AI code
- Fast sandbox startup times
- Python and JavaScript SDKs available
- Open source with managed cloud option
- Customizable environment templates
Cons
- Requires developer knowledge to integrate
- Usage-based pricing can scale with heavy workloads
- Limited value outside AI/agent use cases
Battle record
Across 4 battles in the Pantheon.
Last 4 battles
Reviews
Average from 4 ratings.
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Solid for our team
We rolled this out across the team last quarter and strong isolation for running untrusted AI code. Custom environment templates fits neatly into how we already work, and designed for AI agents and code interpreters removed a step we used to do by hand. but it has held up under daily use.
Use it every day
Honestly didn't expect to like it this much. Isolated cloud sandbox environments is exactly what I needed, and strong isolation for running untrusted AI code. I do wish limited value outside AI/agent use cases, but I reach for it almost every day now and it just clicks.
Solid for our team
We rolled this out across the team last quarter and open source with managed cloud option. Designed for AI agents and code interpreters fits neatly into how we already work, and designed for AI agents and code interpreters removed a step we used to do by hand. Limited value outside AI/agent use cases, which is the main caveat, but it has held up under daily use.
Compared a few options
Evaluated this against two competitors. Where it wins: file system and process access and fast sandbox startup times. Where it lags: limited value outside AI/agent use cases. On balance the feature set — especially custom environment templates — justifies the 4 stars for our use case.
Q&A
What are the pros and cons of E2B?
Pros include strong isolation for running untrusted AI code, fast sandbox startup times, and customizable environment templates. Cons include requiring developer knowledge to integrate and usage-based pricing that can scale with heavy workloads.
Asked by Wanjiru Kamau · Jan 26, 2026
Is E2B open source?
Yes, E2B is open source at its core, with managed cloud infrastructure available for production use.
Asked by Sofia Lindqvist · Jan 24, 2026
How do I integrate E2B?
E2B provides SDKs in Python and JavaScript, making it straightforward to integrate sandboxes into existing AI workflows. Customizable templates also let teams preconfigure dependencies and tooling.
Asked by Ulrik Madsen · Dec 29, 2025
What is E2B used for?
E2B is used for running AI-generated code and autonomous agents in secure cloud sandboxes. It is aimed at teams building agentic applications, code interpreters, and data analysis assistants.
Asked by Dmitri Volkov · Dec 22, 2025
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