Open-source secure code-execution sandbox for AI agents — spin up a fresh Linux VM in under 200ms, hand your agent a Python/Node/Bash environment, and get back files, plots, and results without ever exposing your infrastructure.
Open-source secure code-execution sandbox for AI agents — spin up a fresh Linux VM in under 200ms, hand your agent a Python/Node/Bash environment, and get back files, plots, and results without ever exposing your infrastructure.
E2B is the code-interpreter backbone for a large fraction of modern AI agents. Each sandbox is a small Firecracker microVM with its own filesystem, network, and process table, spun up in roughly 150-200 milliseconds; you install packages, run code, upload files, and stream stdout/stderr through simple Python and JavaScript SDKs. It's the same primitive that powers ChatGPT-style code interpreter but under your control: agent runs untrusted code inside E2B, you get isolation and reproducibility. E2B ships a Desktop sandbox that includes a full Xfce desktop for computer-use agents (Anthropic's Computer Use, OpenAI operator-style demos), Custom Templates (Dockerfile-based sandbox images), long-running background processes, and persistent storage between runs. Pricing has a free Hobby tier (100 hours/mo compute, small vCPU/memory quotas), Pro ($150/mo credits pool), and Enterprise plans with dedicated capacity, SOC 2, and on-prem options. E2B is open source under Apache 2.0 and can be self-hosted, but the hosted product is what most teams use. If your agent needs to run code the model wrote — data analysis, chart generation, script execution, computer use — E2B is the safest and fastest way to give it that capability.
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E2B sets the gold standard for secure AI code execution with revolutionary Firecracker microVM technology, industry-leading performance, and comprehensive developer tooling. The lack of GPU support and ephemeral storage are notable limitations, but for secure general-purpose code execution by AI systems, E2B delivers unmatched security and performance.
secure AI sandboxes is a core E2B capability covered in the staged data and revised against the latest curl research available for this run.
Use Case:
Adding code interpreter features inside AI products.
virtual computers for agents is a core E2B capability covered in the staged data and revised against the latest curl research available for this run.
Use Case:
Running isolated research, data analysis, and file transformation workloads.
code interpreter infrastructure is a core E2B capability covered in the staged data and revised against the latest curl research available for this run.
Use Case:
Giving computer-use or background agents temporary virtual machines with quotas.
computer-use and background agents is a core E2B capability covered in the staged data and revised against the latest curl research available for this run.
Use Case:
Adding code interpreter features inside AI products.
Secure MCPs is a core E2B capability covered in the staged data and revised against the latest curl research available for this run.
Use Case:
Running isolated research, data analysis, and file transformation workloads.
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Through early 2026, E2B has expanded its Desktop sandbox offering to better support the wave of computer-use agents from Anthropic, OpenAI, and open-source projects, with improved VNC streaming and lower-latency input handling. The platform has deepened native integrations with the Anthropic Claude tool-use API and the Vercel AI SDK, and broadened its enterprise footprint with additional regions and SOC 2 Type II attestation. Custom template build times have been reduced, and per-second billing granularity plus larger memory tiers now make it viable for heavier data-analysis and ML inference workloads inside a sandbox.
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