Gibil vs Daytona
Container sandbox vs full VM. Two ways to give an agent a Linux environment.
Daytona and Gibil both give an agent somewhere to run code. The line between them is the shape of the box: Daytona ships a container sandbox, Gibil ships a full VM. That difference cascades into what the agent can actually do once it's inside, how long it can live there, and how it's isolated.
Container sandbox vs full VM
Daytona runs your agent inside a container-style sandbox with a sub-90ms cold start (daytona.io). The runtime is Sysbox + runc — a hardened OCI container with namespaced systemd and dockerd-in-container, but the kernel is shared with the host. Daytona's "dedicated kernel, filesystem, network stack" marketing refers to namespaced kernel resources, not a separate kernel image. Fast to boot, easy to scale, indefinite session lifetime. The tradeoff is isolation: a container is a process group with namespaced filesystem and network, not its own machine.
Gibil runs your agent on its own Hetzner VM — dedicated kernel, real network stack, full root, real systemd, Docker-in-Docker that doesn't need privileged mode. Boot is 30–90 seconds. The trade is honest: you pay cold start to get a real Linux box.
For an agent doing real work — install dependencies, start services, run tests, possibly break things — the shape that matches the threat model is a VM, not a container. When the agent is asleep on the work and your attention isn't there, the blast radius is whatever the box lets it touch. A real VM has nothing to leak into.
At a glance
| Gibil | Daytona | |
|---|---|---|
| Shape | Full VM (own kernel) | Sysbox container (shared kernel) |
| Docker-in-Docker | Yes — native, no privileged dance | Yes |
| SSH | Yes — first-class | Yes — token-based (Daytona docs) |
| Own public IP | Yes | No |
| Persistent codebase | Yes | Yes |
| MCP server | Yes | Yes |
| Primary interface | CLI, MCP, SSH | SDK / API / CLI / MCP |
| Resource ceiling | 48 vCPU / 192 GB | Configurable, no published cap |
| Cold start | 30–90s | <90ms (vendor claim) |
| Lifetime | 15m to 30d, extendable | Indefinite |
| Price (2 vCPU / 4 GB) | ~$0.008/hr | ~$0.17/hr |
| BYOC | Yes — your account (Hetzner + Vultr today, more clouds on the roadmap) | No |
Pricing snapshot: 2026-05-05. Compared per-hour because that matches Gibil's shape (sessions of minutes to days), not per-second sandbox calls. Daytona's per-CPU-hour + per-GB-RAM-hour rates work out to ~$0.166/hr at 2 vCPU / 4 GB — see Daytona pricing for current numbers.
When Daytona is the right tool
- Sub-100ms cold start matters for high-concurrency workloads
- Container-grade isolation is acceptable for the workload
- You want a managed platform with no infrastructure to operate
- Your agent's tasks fit comfortably inside a container — no kernel modules, no systemd services that fight a container runtime
- Indefinite session lifetimes with SDK-first integration
When Gibil is the right tool
- The agent needs the full Linux toolbox —
apt installreal packages, run real services, use Docker-in-Docker for integration tests - You want VM-level isolation when the agent is running unattended
- BYOC matters — your code stays on your own account (Hetzner + Vultr today)
- You need agent-agnostic infrastructure — any MCP-compatible agent, not locked into one SDK
- Cost matters at scale (~20× cheaper at 2 vCPU / 4 GB)
Next steps
- Gibil vs E2B — the microvm-shaped alternative
- Gibil vs Claude Code Cloud Sessions — Anthropic's managed VM option
- Quick Start — try Gibil in 5 minutes