Does E2B run my LLM, or just the code?

Just the code and tools — you connect your own LLM. E2B is model-agnostic sandbox infrastructure.

Can a sandbox keep state between runs?

Yes. Pausing saves both the filesystem and memory, and paused sandboxes are kept indefinitely until you resume them.

HostingOpen sourceNot yet hands-on tested

E2B

An open-source, secure environment with real-world tools for enterprise-grade agents.

What it is

E2B provides isolated, secure Linux sandboxes created on demand so AI agents can execute code, process data, and run automations. It is infrastructure — an SDK plus hosted cloud — rather than an agent framework or a model.

At a glance

7/7 facts sourced

Pricing: Hobby (free) includes a one-time $100 usage credit, up to 1-hour sessions, and 20 concurrent sandboxes. Pro is $150/mo + usage (24-hour sessions, up to 100 concurrent). Usage is per-second (e.g. 1 vCPU at $0.000014/s).source ↗
Hosting model: Hosted cloud that spins up on-demand secure Linux VM sandboxes reachable both internally and via a sandbox URL; self-hostable given the open-source codebase.source ↗
Memory & state: Sandbox persistence — pausing saves both filesystem and memory state, and connect() resumes the identical state, with paused sandboxes kept indefinitely. This is infrastructure state, not agent/LLM memory.source ↗
MCP support: Nativesource ↗
Integrations: First-party Python and JS/TS SDKs, Templates for defining environments, and MCP tools from a Docker catalog (Browserbase, Stripe, GitHub, Notion, and more).source ↗
Model providers: Model-agnostic — you bring your own LLM; E2B runs the code and tools, not the model.source ↗
Open source: Yessource ↗

3.7of 5

Editorial scorecard

Overall 3.7 / 5

Our opinion — the same 0–5 rubric is applied to every platform, including Alfe. See the rubric.

Developer experience4/5

Pricing transparency & value4/5

Scalability4/5

Memory & state3/5

Integrations3/5

MCP nativeness4/5

Strengths

Pause/resume preserves both filesystem and memory, retained indefinitely.
Free Hobby tier with a $100 credit and 20 concurrent sandboxes; transparent per-second pricing.
Open source with first-party SDKs and an official MCP server.

Trade-offs

Infrastructure only — no LLMs, orchestration, or agent memory; you bring your own.
A single continuous session is capped (1 hour on Hobby, 24 hours on Pro) before you must pause and resume.
Usage-based per-second cost plus the $150/mo Pro base is harder to forecast than flat pricing.

Our take

Editorial opinion — not a hands-on test result

In our opinion, E2B is a strong pick when you specifically need secure, disposable sandboxes for agent-run code and want to bring your own model and orchestration. It is not a full agent platform, so treat it as a building block. The pause/resume persistence is a genuine differentiator for long-running or resumable agent tasks.

FAQ

Does E2B run my LLM, or just the code?: Just the code and tools — you connect your own LLM. E2B is model-agnostic sandbox infrastructure.
Can a sandbox keep state between runs?: Yes. Pausing saves both the filesystem and memory, and paused sandboxes are kept indefinitely until you resume them.

Compare E2B

Sources

E2B homepage · accessed 2026-07-01
E2B pricing · accessed 2026-07-01
E2B sandbox persistence docs · accessed 2026-07-01
E2B on GitHub · accessed 2026-07-01

The Agent Examiner editorial · last updated 2026-07-01. Facts are drawn from each vendor’s own public materials; scores are our editorial opinion (methodology).

Product and company names are trademarks of their respective owners and are used here only to identify the products under discussion.