Daytona provides an isolated runtime for executing AI-generated code and agent workflows. Its homepage states that sandbox creation takes under 90ms, and its programmatic controls include process execution, file-system operations, Git integration and built-in language-server support. SDK examples or interfaces are shown for Python, TypeScript, Ruby, Go and Java. Listed uses include AI evaluations, code interpreters, coding agents and data analysis. The CLI supports macOS, Linux and Windows; MCP server documentation lists Claude, Cursor and Windsurf as supported agents. Network controls include IPv4 CIDR and domain allow lists, blocking all outbound traffic, and chained outbound proxies. Organization-scoped secrets are encrypted at rest and injected as opaque placeholders, with plaintext substituted only for allowed HTTPS hosts. Daytona offers free and usage-based options. The usage-based plan lists charges per second for compute, memory, storage and Windows, with the first 5 GiB of storage free and $200 in free compute included. Enterprise pricing is available by contacting sales; its listed features include larger limits, SSO, audit logs and BYOC.
Who it is for
Daytona suits developers and teams running AI-generated code, agent workflows, evaluations or data-analysis tasks. It offers hosted and self-hosted options, with CLI support on macOS, Linux and Windows.
What is good
- Execution controls cover processes, files and Git.
- SDK interfaces are shown for five languages.
- Network rules can block all outbound traffic.
- First 5 GiB of storage is free.
What to know first
- VPN connections require Tier 3 or higher.
- Enterprise pricing requires contacting sales.
- GPU rates vary by model and preemptible or on-demand use.
Verdict
Daytona combines isolated code execution with APIs, language SDKs and configurable network controls. Its usage-based pricing lists compute and storage rates, while enterprise pricing and VPN access have additional conditions.
Daytona plans and pricing
All plansCompared on coding playgrounds
- Workspace config
- dockerfile
- VCS hosts
- multiple
- Prebuilds
- Yes
- Persistent storage
- Yes
- Self-hosted option
- Yes
- GPU workspaces
- Yes
- JetBrains support
- Yes
