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The best open source alternative to Daytona is E2B. If that doesn't suit you, we've compiled a ranked list of other open source Daytona alternatives to help you find a suitable replacement. Other interesting open source alternatives to Daytona are: Beam and OpenComputer.
Daytona alternatives are mainly AI Sandboxes but may also be GPU & Compute Platforms. Browse these if you want a narrower list of alternatives or looking for a specific functionality of Daytona.
Provide AI agents with secure, isolated sandboxes featuring real-world tools, code execution, and enterprise-grade security. Trusted by 88% of Fortune 100 companies.

E2B delivers secure cloud environments specifically designed for enterprise AI agents, providing isolated sandboxes where agents can safely execute code, access real-world tools, and perform complex tasks without compromising security.
Key capabilities include:
Perfect for advanced AI use cases:
Trusted by leading organizations including 88% of Fortune 100 companies, E2B integrates seamlessly with OpenAI, Anthropic, Mistral, LangChain, and custom models. The platform offers flexible deployment options including BYOC, on-premises, and self-hosted solutions to meet enterprise compliance requirements.
Run GPU inference, task queues, and sandboxes on serverless infrastructure with sub-second cold starts, autoscaling, and support for your own AWS, GCP, or bare metal.

Beam is a GPU compute platform built specifically for AI workloads. It handles serverless inference, durable task queues, and isolated sandboxes, all defined in Python without Dockerfiles or YAML config. You can run on Beam's cloud or connect your own AWS, GCP, or bare metal accounts and let Beam orchestrate across all of them.
The core differentiator is boot time. Beam uses memory snapshots to restore GPU containers in under a second, up to 35× faster than a traditional cold start. That matters when you're running inference at scale or building agent pipelines where latency compounds quickly.
Key capabilities:
Compared to tools like Modal or dstack, Beam leans hard on the sandbox and snapshotting story, which makes it a natural fit for agent frameworks that need stateful, parallelizable execution environments.
Pricing starts at $0.69/hr for a 4090, with $30 in free credits refreshed monthly. SOC 2 Type II certified.
Provides always-on virtual machines for AI agents with full OS access, persistent state, elastic CPU/memory resizing, and instant checkpoints.

Most AI agents run on disposable sandboxes: spin up, execute a task, disappear. That works for throwaway scripts. It breaks down the moment an agent needs to remember what it installed, keep files between sessions, or pick up mid-task after a pause. OpenComputer is built for that second category.
Each VM is a real machine with a full filesystem and full OS access. It stays running until you explicitly stop or delete it. No timeouts, no teardowns. State persists across sessions without any extra plumbing on your end.
Key capabilities:
OpenComputer targets teams building agent platforms where end users expect continuity. Think coding assistants like Devin or Lovable, where a user's environment needs to remember yesterday's installs and today's open files. Ephemeral sandboxes give isolation. OpenComputer gives isolation plus persistence, without forcing you to manage state externally.
Pricing starts at $0.004 per minute for a 4 GB / 1 vCPU configuration. Disk beyond the included 20 GB is metered separately, and hibernated VMs don't accrue compute charges.
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