E2B
Let your AI agent execute real code in a secure cloud sandbox: spins up in 150ms, runs Python and JavaScript safely, and tears down cleanly when done.
The verdict on E2B: Developers who need agents to run untrusted code safely without touching their own infrastructure E2B's job is to let an AI agent execute real code without touching your infrastructure or running untrusted scripts in your environment. Pricing: Pro $150/month + compute / CPU $0.000014/vCPU-second / RAM $0.0000045/GiB-second / Hobby $0 base + usage; one-time $100 credit.
Best For
Developers who need agents to run untrusted code safely without touching their own infrastructure
Standout Feature
Sandboxed cloud VMs spin up in under 150ms, fast enough for interactive agentic reasoning loops
TL;DR
A clean solution to unsafe code execution, sandboxes are ephemeral by default so persistent state needs explicit setup.
Alternatives
Fit Score: use-case reference
How this is scoredE2B scored 1 to 5 on five dimensions for the named use cases below. Part of our catalog-wide use-case reference, not a product-quality review rating.
A developer building an agent that needs to run untrusted code safely without touching their own infrastructure
4.2/5- Capability
- 5/5
- Reliability
- 4/5
- Value
- 4/5
- Ease
- 4/5
- Compatibility
- 4/5
E2B's sandboxed cloud VMs spin up in under 150ms, fast enough for interactive agentic reasoning loops, which the tool's own take calls the clean solution to unsafe code execution without infrastructure risk.
An agent that needs persistent state across sandbox sessions without extra configuration, or a very long-running high-compute job
2.4/5- Capability
- 2/5
- Reliability
- 3/5
- Value
- 2/5
- Ease
- 3/5
- Compatibility
- 2/5
Cons note sandboxes are ephemeral by default so persistent state requires explicit config, and metered compute remains chargeable beyond the one-time Hobby credit and is separate from the Pro base fee.
Editorial judgment grounded in this tool's own published pricing, features, and our existing pros and cons, not a certification or a measured benchmark. Product quality is assessed separately under our review methodology.
Overview
Not yet reviewedProduct quality is assessed from original evidence. How reviews work.
E2B provides sandboxed code execution environments for AI agents: secure, isolated cloud VMs that spin up in under 150ms and let agents run, test, and iterate on code without touching your infrastructure. Each sandbox is fully ephemeral and isolated so agents can execute untrusted code safely. Integrates with Claude, GPT-4o, and any agent framework that generates code as part of its reasoning loop.
Pro costs $150/month plus metered compute at $0.000014/vCPU-second and $0.0000045/GiB-second in USD; the subscription raises limits and grants no additional usage credits. Hobby has a $0/month base and a one-time $100 starter usage credit, not a $100 charge or recurring free compute. Optional concurrency add-ons cost extra.
The source of the legacy catalog rating and review count has not been substantiated. Neither is presented here as a verified review rating or included in review structured data.
Workflow Fit Scores are separate, use-case-specific editorial judgments, not user-review averages. Read the Fit Score methodology.
- • Solves unsafe code execution cleanly: no infrastructure risk
- • Fast enough (150ms) for interactive agentic reasoning loops
- • One-time $100 Hobby usage credit supports development and prototyping
- • Ephemeral by default, persistent state requires explicit config
- • Sandbox compute is metered, long-running agents can get expensive
- • Network access inside sandbox may need allowlisting for enterprise use
Key Features
- Sandboxed cloud VMs with 150ms cold start times
- Python, JavaScript, Bash, and custom Docker environments
- File system access, network calls, and package installation inside sandbox
- SDK integrations for Claude, GPT-4o, Gemini, and LangChain
- Persistent sandbox state across multi-step agent runs
- Custom sandbox templates via Dockerfile
Trust & Data
Verified 2026-09
- Training on your data
- Not publishedE2B's crawlable privacy policy is a generic legal-template policy covering only website-visitor data such as name, email, GitHub username, and usage analytics, and says nothing about whether sandbox code, files, or session data are used for training. E2B's dedicated trust center, which third-party reviews claim lists SOC 2 Type II, ISO 27001, HIPAA, and GDPR, renders as an essentially empty JS-only shell when fetched directly, so none of those certification claims could be independently confirmed on the vendor's own retrievable content.
- Compliance
- Not published
- Retention
- The privacy policy states automatically collected non-personal usage data is retained for about 13 months; this covers only website analytics, not sandbox or session data, which has no retention statement anywhere on the vendor's own site.
- Export
- Partial export
Sources: e2b.dev, trust.e2b.dev
As published by the vendor. Verify independently before purchase decisions.
Our Take
Sandboxed cloud VMs spin up in under 150ms, which is fast enough for interactive agentic reasoning loops where the agent writes code, runs it, reads the output, and iterates. Each sandbox is ephemeral and isolated by default. That default is also the main constraint: if your agent needs state to persist across sandbox sessions, you have to set that up explicitly. Hobby has a $0/month base with a one-time $100 usage credit, one-hour sessions, and up to 20 concurrent sandboxes. Pro costs $150/month to raise limits, plus CPU and RAM usage; upgrading grants no additional credits. Long-running agents therefore need a compute budget, not just a subscription budget. The right fit is a developer building an agent that needs safe code execution without the infrastructure overhead.
Workflows Using This Tool
Step-by-step playbooks whose entries name E2B. The step shown is where the workflow uses it.