Daytona
Usage BasedSecure and elastic infrastructure for running AI-generated code.
Published 1 October 2026
Scores
Popularity3/5
Its former open-source repository passed 65K GitHub stars and it is named alongside E2B and Modal in nearly every sandbox comparison, though the category itself is still new to most developers.
Learning Curve2/5
Creating a sandbox and running code is a couple of SDK calls in any of four languages, and default snapshots already include Python, Node, and their language servers.
Flexibility4/5
Any Docker image, declarative builds, persistent or throwaway sandboxes, volumes, GPUs, computer use, and an MCP server cover most agent designs, within the limits of a managed platform whose code is no longer open.
Performance5/5
Sub-100 ms starts from snapshots lead the category in independent comparisons, and massive parallel creation is a core design goal.
Portability2/5
Closed-source since June 2026 with a proprietary API and control plane, so leaving means rewriting against another provider's SDK. Customer-managed runners keep compute, but not control, in-house.
About Daytona
Daytona is sandbox infrastructure for AI agents: an API for spinning up isolated environments where agents run the code they generate, work with files and Git, and use tools, then keep or discard that environment. It began as an open-source development-environment manager and relaunched in 2025 around agent workloads. It is one of the built-in sandbox providers in the OpenAI Agents SDK, and its customers include LangChain, Writer, and SambaNova.
Its headline is speed. Sandboxes start from snapshots in under 100 milliseconds, the fastest cold start among the major providers, which suits agents that create many short-lived environments in parallel. Sandboxes are built from any OCI or Docker image, or declared in code through a builder, and unlike most rivals they can persist without a time limit, with volumes for shared data and snapshots to capture a prepared environment and clone it. Built-in APIs cover process execution, file operations, Git, language-server features for code intelligence, computer use through a virtual desktop, and an MCP server; GPU-backed sandboxes are available for heavier jobs.
Developers drive it through Python, TypeScript, Go, and Ruby SDKs or a CLI. Billing is per second for CPU, memory, and storage, with free starter credits, and Customer Managed Compute lets enterprises run the sandbox runners on their own machines while Daytona operates the control plane.
In June 2026 Daytona took its production codebase closed-source, citing the risk of AI-assisted vulnerability hunting against public isolation code. The old AGPL repository is archived, and the last open release lives on as the community fork Nightona. Teams that need a fully open, self-hostable sandbox now usually look at E2B or OpenSandbox; Daytona's pitch is raw speed and long-lived sandboxes as a managed service.
Key Features
- Sandbox starts in under 100 ms from snapshots
- Sandboxes that can persist with no fixed time limit
- Build from any OCI or Docker image or a declarative code builder
- Snapshots and volumes for reusable environments and shared data
- Process, file, Git, language-server, and computer-use APIs
- Python, TypeScript, Go, and Ruby SDKs plus a CLI
- GPU-backed sandboxes for heavier workloads
- Customer Managed Compute runners on your own machines
Pros
- Fastest cold starts of the major sandbox providers, useful for highly parallel agents
- Long-lived sandboxes suit agents that return to the same workspace across sessions
- Built-in Git and language-server APIs cover coding-agent needs without extra setup
- Free starter credits and no minimum spend make it easy to trial
Cons
- Closed-source since June 2026, with the old public repo archived
- Full self-hosting is gone; own-hardware runners still depend on Daytona's control plane
- Container-based sandboxes share a host kernel, a weaker boundary than E2B's microVMs
- Wall-clock billing charges while a sandbox sits idle waiting on the model
Daytona Pricing
Usage Based- · $200 in compute credits on signup, no card required
- · 5 GB of storage free
- · Per-second billing for vCPU, memory, and storage
- · About $0.05 per vCPU-hour and $0.016 per GiB-hour of memory
- · GPU sandboxes billed separately
- · Customer Managed Compute on your own runners
- · Custom limits and support
Tools Related to Daytona
Works well with Daytona(1)
Daytona builds sandboxes from any Docker or OCI image, so an existing project image becomes the environment an agent runs code in.
Integrates with Daytona(2)
The OpenAI Agents SDK ships a native Daytona adapter, letting its sandbox agents execute commands and work with files in a Daytona sandbox.
Hermes Agent includes Daytona as one of its terminal backends, running the agent's commands in a Daytona sandbox that hibernates when idle.
Alternatives to Daytona(2)
E2B isolates each sandbox in its own Firecracker microVM and is open source and self-hostable; Daytona starts container-based sandboxes faster and lets them persist without a time limit, but is a closed-source managed service.
Daytona specialises in agent sandboxes, with the fastest starts and environments that can persist indefinitely; Modal offers sandboxes as one part of a serverless compute platform, with GPUs and model serving alongside.