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Both give you fast, isolated Linux sandboxes for AI agents. Daytona is fully open source (Apache 2.0) and can be self-hosted on your own Kubernetes; E2B is closed-source and hosted-only. E2B has a larger community and more polished desktop templates today; Daytona wins on self-hosting and per-branch dev environments.
Yes. Daytona ships a documented Kubernetes install and the runtime is Apache 2.0. You'll own the K8s ops, image registry, and GPU capacity — worth it if data can't leave your VPC.
You describe the environment in a devcontainer.json or short config file. Daytona hydrates the sandbox from that spec every run, so the environment is reproducible and diffable rather than snapshot-frozen.
On the managed cloud and self-hosted, yes — with GPU-typed pools. GPU quotas and pricing are contract-based on the enterprise tier.
Yes. Daytona integrates natively with Claude Code, Cursor, and Cline as an execution backend, and exposes an MCP server so any MCP-compatible client can offload code execution to a sandbox.
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