What is OpenComputer?
OpenComputer provides persistent, always-on virtual machines designed specifically for AI agents.Unlike sandboxes, it offers a full operating system and filesystem, allowing agents to maintain state across sessions.
Agents can dynamically resize memory and CPU resources in real-time to match workload demands.The VMs support hibernation and wake-up functionality, preserving the agent's exact state upon resumption.This persistence eliminates issues like repeated installations or lost data.
It’s built for seamless integration with frameworks like Claude Agent SDK.OpenComputer scales efficiently within cloud environments and offers flexible storage options up to 20GB.It provides a robust foundation for complex, long-running agent applications, removing the limitations of disposable sandboxes.
These VMs are ideal for scenarios where agents require consistent access to files and persistent data.
OpenComputer user reviews
Would you recommend OpenComputer?
OpenComputer's key features
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Scalable on-demand compute combining VM-level isolation with sandboxed execution
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Type-1 ephemeral sandboxes for executing untrusted code, returning stdout, and destroying the environment per invocation
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Type-2 persistent sandboxes for long-lived agent sessions that preserve state and enforce security boundaries
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Integration with CLI-based SDKs and agent frameworks enabling file read/write, process execution, and use of runtime tooling
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Configurable operator controls for latency vs security tradeoffs (warmed pools vs per-run sandboxes, VM vs container isolation)
OpenComputer use cases
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Execute untrusted user extensions and third-party plugins for LLM agents in fast ephemeral VM sandboxes, ensuring kernel-level isolation, low-latency cold starts, and comprehensive auditing to prevent cross-tenant leaks
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Run long-lived, stateful agent sessions that preserve memory and filesystem context across interactions using persistent VM sessions with predictable isolation and SDK integration for orchestrating complex multi-step workflows
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Implement secure CI/CD and automated evaluation for models and agent code by launching scalable, auditable sandboxed VMs for reproducible tests and adversarial inputs, combining sandboxed code execution with logging and integration into existing developer toolchains
Who is it for?
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Llm agent developers
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Ml engineers
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Product managers
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Platform engineers
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Security teams
