Daytona
Last verified 2026-07-26
Daytona pivoted from cloud dev environments to AI-agent infrastructure in early 2025 and is the most prominent open-source entrant by GitHub traction (70K+ stars, $24M Series A). It uses Docker-container isolation, persistent Running/Stopped/Archived workspace lifecycles, mid-execution snapshots, Computer Use, and GPU access.
Key specs
| Isolation | Docker container |
| Cold start | 90ms |
| Price / vCPU-hr | $0.05 |
| Pricing model | Usage-based |
| GPU | H100 ~$3.95/hr |
| Session limit | Persistent (lifecycle-managed) |
| Persistence | Persistent workspaces, snapshots |
| Languages | Python, JavaScript/TypeScript, any |
| MCP support | Yes |
| Integrations | OpenAI Agents SDK, LangChain |
| Deployment | Managed cloud + open source |
| Free tier | Free credits |
| GitHub stars | 70K+ |
| Funding | $24M Series A |
Strengths
- Open source (70K+ stars)
- ~90ms creation
- Persistent workspaces
- GPU available
Trade-offs
- Container isolation is weaker than microVM
- Younger managed cloud
Best for: Teams that want open source, persistent stateful workspaces, and GPU access.
How Daytona works
Daytona isolates each workspace in a Docker container, which shares the host kernel, so the boundary is lighter than a microVM but comes up fast: new workspaces start in about 90ms. Workspaces are persistent and move through a Running, Stopped, and Archived lifecycle, so an agent can stop one and pick it back up with state intact. You can snapshot mid-execution, attach an H100 GPU, and drive it over MCP. Daytona pivoted from cloud dev environments to agent infrastructure and is open source, so self-hosting is an option alongside the managed cloud.
Pricing in practice & watch-outs
Pricing is usage-based at about $0.05 per vCPU-hour, with H100 GPU time around $3.95 an hour, and there are free credits to start. The main trade-off is isolation: Docker containers share the host kernel, so the separation between a workload and the host is weaker than a microVM boundary. For running untrusted agent code that is worth weighing. The managed cloud is also newer than the project's GitHub traction (70K+ stars) might suggest, so it carries less operational track record. If that matters, the open-source route lets you run it yourself.
Head-to-head
Alternatives to Daytona
See the full Daytona alternatives comparison →
Sources: Daytona docs ↗ · Daytona pricing ↗
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