Daytona vs OpenAI Containers
Daytona is a cloud where you create sandboxes through its API and keep them as long as you want, with Docker, SSH, GPUs and Windows on offer. OpenAI Containers are short-lived boxes inside OpenAI's model API: the model runs Python or shell commands there, and the box expires after 20 minutes without use.
The companies and products
Daytona
Daytona is a cloud for running AI-generated code: you create sandboxes from code through its API and SDKs.
By default a Daytona sandbox is a Linux container with its own namespaces and reserved vCPU, memory and disk. You can also pick a Linux VM class (pause, fork, memory snapshots, /dev/kvm), a Windows VM class, or a GPU class with Nvidia and AMD cards. It is built for teams that run agent code, code interpreters and evals through Python, TypeScript, Ruby, Go or Java SDKs.
- Founded
- 2023
OpenAI Containers
OpenAI Containers are the sandboxes OpenAI runs for its own model tools: Code Interpreter, Hosted Shell and the Agents API's hosted sandbox.
This is a different kind of product from boat: a tool inside OpenAI's model API, not a machine you rent. You create a container through the API or let a Responses call make one, and the model runs Python or shell commands in it on a fixed Debian 12 image without sudo, until it expires after 20 minutes without use. It is built for apps that already call OpenAI models and want them to run code, read files and make charts without running any servers.
Which use cases each one fits
For each use case, Battleships prices every sandbox provider on the same workload and sorts them from the cheapest monthly bill up. “15th cheapest of 367” means 14 of the other 366 providers run that workload, with every feature it needs, for less. “With limits” means the provider runs it but misses something, so it is listed after every full match. Open a use case for its whole ranking and what each provider misses.
| Use case and its workload | Daytona: price rank | OpenAI Containers: price rank | boat: price rank |
|---|---|---|---|
| Software factory 100 at once · 4 vCPU / 8 GB · 2,200 sessions of 8 h a month Daytona fits a coding agent that installs, builds and runs Docker for days; an OpenAI container has no root, no Docker and loses its files after 20 idle minutes, and boat ranks 3rd. | 15th cheapest of 367 $4,111 a month | 356th of 367, with limits $17,371 a month | 3rd cheapest of 367 $634 a month |
| Always-on AI employees 50 machines 24/7 · 2 vCPU / 4 GB An assistant that lives on its machine all month fits Daytona; an OpenAI container has to be touched every 20 minutes or it is deleted with its data. | 24th cheapest of 366 $6,104 a month | 341st of 366, with limits $13,140 a month | 5th cheapest of 366 $657 a month |
| Code interpreter bursts 100 at once · 1 vCPU / 2 GB · 200,000 sessions of 1 min a month This is the job OpenAI Containers are built for, but Daytona ranks 25th of 345 at $271 a month here against $6,000 a month for OpenAI, which also bills model tokens on top. | 25th cheapest of 345 $271 a month | 194th of 345, with limits $6,000 a month | 186th of 345, with limits $2,000 a month |
| Sandboxes for your users 300 at once · 2 vCPU / 4 GB · 30,000 sessions of 23 min a month 300 sandboxes of 2 vCPU need 600 vCPU, more than Daytona's Tier 4 pool of 500, and OpenAI containers take no inbound connections and publish no concurrency limit; boat ranks first. | 154th of 361, with limits $2,000 a month | 361st of 361, with limits $3,780 a month | Cheapest of 361 $209 a month |
| RL rollouts 1,000 at once · 2 vCPU / 4 GB · 1,000,000 sessions of 3 min a month | 130th of 360, with limits $8,261 a month | 191st of 360, with limits $30,000 a month | 34th of 360, with limits $2,000 a month |
| Agent evals 250 at once · 4 vCPU / 8 GB · 15,000 sessions of 20 min a month | 189th of 364, with limits $2,000 a month | 360th of 364, with limits $5,760 a month | 10th cheapest of 364 $200 a month |
| CI runners 40 at once · 8 vCPU / 16 GB · 6,000 sessions of 12 min a month Daytona caps a sandbox at 4 vCPU by default, and OpenAI documents no Docker or root and starts Code Interpreter containers with no internet; boat allows 8 vCPU from the $20 plan. | 308th of 377, with limits $805 a month | 345th of 377, with limits $1,728 a month | 4th cheapest of 377 $86 a month |
| 24/7 dev boxes 1 machine 24/7 · 4 vCPU / 8 GB Daytona keeps a dev box's disk but bills it while stopped; OpenAI containers have no SSH and no persistent disk; boat ranks 18th with a stopped sandbox that costs nothing. | 183rd of 368, with limits $245 a month | 362nd of 368, with limits $1,051 a month | 18th cheapest of 368 $26 a month |
| Computer-use agents 50 at once · 4 vCPU / 8 GB · 20,000 sessions of 15 min a month Daytona has a VNC desktop and a computer-use API on Linux and Windows, OpenAI has a hosted browser inside the Agents API beta, and boat streams a 60fps desktop you can embed. | 26th cheapest of 369 $1,198 a month | 351st of 369, with limits $5,280 a month | 6th cheapest of 369 $200 a month |
| Browser-use agents 50 at once · 2 vCPU / 4 GB · 30,000 sessions of 10 min a month | 93rd of 367, with limits $598 a month | 328th of 367, with limits $1,440 a month | 7th cheapest of 367 $200 a month |
| Scraping & bots (startup scale) 50 at once · 1 vCPU / 2 GB · 100,000 sessions of 3 min a month | 38th cheapest of 346 $404 a month | 328th of 346, with limits $1,755 a month | 6th cheapest of 346 $90 a month |
| Mass scraping & bots (undetectable) 1,000 at once · 1 vCPU / 2 GB · 3,000,000 sessions of 2 min a month | 202nd of 338, with limits $8,073 a month | 311th of 338, with limits $35,100 a month | 71st of 338, with limits $1,800 a month |
| Parallel red teaming 200 at once · 2 vCPU / 4 GB · 5,000 sessions of 30 min a month | 12th cheapest of 360 $2,000 a month | 308th of 360, with limits $870 a month | 2nd cheapest of 360 $200 a month |
| GPU eval jobs 10 at once · 8 vCPU / 32 GB · 500 sessions of 30 min a month Only Daytona fits: it rents Nvidia and AMD GPUs by the hour, while OpenAI Containers and boat have none. | 20th cheapest of 98 $1,190 a month | Can't run it | Can't run it |
| macOS agents 5 at once · 4 vCPU / 8 GB · 1,000 sessions of 20 min a month | Can't run it | Can't run it | Can't run it |
Key features
| Feature | Daytona | OpenAI Containers | boat |
|---|---|---|---|
| Isolation | Container by default; Linux VM and Windows VM classes have their own kernel | Described as a fully sandboxed virtual machine; hypervisor not named | Every sandbox is a full VM with its own kernel on dedicated AMD Ryzen 9 9950X hosts |
| CPU speed (Node.js build-and-test, 4 vCPU / 8 GB) | 21.52 runs/s on the Linux VM class; the default container class reported no result | Not measured; vCPU per size not published | 26.69 runs/s |
| Root, Docker and nested virtualization | Docker in all classes; /dev/kvm only on Linux VMs, with KVM turned on for your organization | Commands do not run with sudo; no Docker or /dev/kvm documented | Root, systemd, Docker and /dev/kvm on every machine |
| Machine size | Up to 4 vCPU / 8 GiB per sandbox by default, raisable per region | Picked by memory: 1, 4, 16 or 64 GB; vCPU not published (Agents API: 1, 2 or 4 vCPU) | 4 vCPU / 8 GB by default, up to 16 vCPU / 32 GB |
| Files after a stop | Disk kept and billed while stopped; archived containers are free | Data is discarded when the container expires; Agents API keeps only files in /workspace/outputs | Disk saved every minute and on stop; a stopped sandbox costs nothing |
| Lifetime | No session cap by default; optional time to live and idle auto-stop you can turn off | Expires after 20 minutes without use; Agents API sandboxes after an hour without activity | No session cap on paid plans; you set the time to live |
| Pause and fork | Linux VM and Windows: pause, resume and fork with memory kept; containers: no pause or fork | No pause, snapshots or fork | Fork a running sandbox with its disk; resume reboots from disk |
| Custom images | Docker images and declarative builds for containers; VM snapshots from an image | Fixed Debian 12 image; you upload files or skills into each container | Named snapshots of a set-up machine, reused as templates; no Dockerfile builds |
| Inbound access | HTTPS preview URLs on any port, token-protected or public; SSH; no raw TCP or public IP | None; you reach the container only through the API | SSH, token-protected HTTPS URLs for up to 50 ports, raw TCP |
| Outbound internet | Tier 1 and 2 reach only package registries, git hosts and AI APIs; Tier 3 and up get open internet plus per-sandbox allowlists | Code Interpreter and Hosted Shell: off until an admin sets an org domain allowlist; Agents API sandboxes: on by default, can be limited to 1 to 100 hosts | Open internet on every plan; no provider-side allowlist |
| Coding agents | Guides install agents and run them through process exec | Agents API (beta) drives a managed Codex harness from outside, with steering, events and webhooks | Claude Code, Codex, OpenCode and more preinstalled, driven from outside with a prompt, steer and events API |
| Desktop and computer use | VNC desktop (xfce4) and a computer-use API on Linux and Windows | Hosted browser for the Agents API computer_use tool | 60fps desktop and Chromium, computer use and browser control, embeddable stream |
| GPUs and Windows | Nvidia and AMD GPUs from RTX 4090 to B300; Windows VM sandboxes | No GPUs; Linux only | No GPUs; no Windows guests, Wine for Windows apps |
| Regions and your own machines | US and EU, plus dedicated regions or your own machines | US or EU processing for Code Interpreter; Agents API can drive a sandbox you host | EU only: Germany, Finland, France |
Every feature Battleships tracks (43)
| Feature | Daytona | OpenAI Containers | boat |
|---|---|---|---|
| Full VM (own kernel) | No | Yes | Yes |
| Docker inside | Yes | No | Yes |
| Nested virtualization | Yes | No | Yes |
| Root | Yes | No | Yes |
| Systemd | Not published | Not published | Yes |
| Desktop GUI | Yes | Yes | Yes |
| Browser | Yes | Yes | Yes |
| Computer-use API | Yes | Yes | Yes |
| SSH | Yes | No | Yes |
| Persistent disk | Yes | No | Yes |
| Pause/resume | Yes | No | Yes |
| Automatic snapshots | Yes | No | Yes |
| Fork/clone | Yes | No | Yes |
| Live fork (no pause) | No | No | Yes |
| Memory fork | Yes | No | No |
| Custom image (Docker or snapshot) | Yes | No | Yes |
| ≥24 h sessions | Yes | Yes | Yes |
| Idle auto-stop | Yes | Yes | No |
| Wake on request | No | No | No |
| HTTPS preview URLs | Yes | No | Yes |
| Raw TCP inbound | No | No | Yes |
| Public IPv4 | No | No | No |
| Egress allowlist | Yes | Yes | No |
| Secret proxy | Yes | Yes | Yes |
| Secret proxy for any API | Yes | Yes | Yes |
| Preinstalled agents | Yes | No | Yes |
| Agent harness API | No | Yes | Yes |
| MCP server | Yes | No | No |
| GPU | Yes | No | No |
| Windows | Yes | No | No |
| Arm64 | No | No | No |
| Self-hosting | No | Yes | No |
| BYOC | Yes | No | No |
| Open source | No | No | No |
| Scoped API keys | Yes | Not published | Yes |
| Spend limits | Not published | Not published | Yes |
| Usage per sandbox (API) | Yes | No | Yes |
| Audit logs | Yes | Not published | No |
| SSO | Yes | Yes | No |
| SOC 2 | Yes | Yes | No |
| HIPAA | Yes | Yes | No |
| EU data residency | Yes | Yes | Yes |
| Zero data retention | Not published | Not published | Yes |
Performance
In StarSling's public run of 2026-09-29 at 4 vCPU / 8 GB, boat did 26.69 Node.js build-and-test runs per second and Daytona's Linux VM class did 21.52; Daytona's default container class reported no result. OpenAI Containers are not in that benchmark, and OpenAI does not publish how many vCPU each container size gets, so there is no comparable number for them.
Node.js build-and-test loop at 4 vCPU / 8 GB, higher is better. Measured with the open hpc-sandbox-benchmarks suite. Daytona measured on: Linux VM sandbox (same rates; KVM / nested virt per-org feature). OpenAI Containers has no published run in this suite yet, so there is no like-for-like number to compare.
Pricing in five scenarios
Each bill is priced from the providers' public price lists by the open Battleships engine, with the cheapest plan that runs the scenario.
| Scenario | Daytona, a month | OpenAI Containers, a month | boat, a month |
|---|---|---|---|
| One coding agent, workdays 4 vCPU / 8 GB, 50 GB disk, 8 hours a day, 22 days a month, files kept between days | $56 · Tier 3 ($500 top-up) | $228 · API pay as you go · with limits | $20 · $20/mo |
| One agent that never stops 4 vCPU / 8 GB, 50 GB disk, running 24/7 all month | $245 · Tier 3 ($500 top-up) | $1,051 · API pay as you go · with limits | $26 · $20/mo |
| 50 agents in parallel 50 machines of 4 vCPU / 8 GB at once, 8-hour sessions, 1,100 sessions a month, Docker inside | $2,682 · Tier 3 ($500 top-up) | $11,405 · API pay as you go · with limits | $317 · $20/mo × 3 seats |
| Sandboxes for your users 2 vCPU / 4 GB, 30,000 sessions of 10 minutes a month, up to 300 at once | $2,000 · Tier 4 ($2,000 top-up every 30 days) · with limits | $1,620 · API pay as you go · with limits | $200 · $100/mo × 2 seats |
| 1,000 short jobs at once 2 vCPU / 4 GB, 1,000 at once, 3 minutes each, 200,000 jobs a month | $2,000 · Tier 4 ($2,000 top-up every 30 days) · with limits | $6,000 · API pay as you go · with limits | $2,000 · $2000/mo · with limits |
Daytona: Daytona bills per second for the vCPU, memory and disk you reserve, and keeps billing the disk while a sandbox is stopped. You pay from a prepaid wallet: open internet needs a $500 top-up (Tier 3), and the biggest pool needs $2,000 every 30 days (Tier 4).
OpenAI Containers: OpenAI bills each container session by the minute for the memory size you pick, with a 5-minute minimum, and model tokens are billed separately on top. There is no plan fee; vCPU per size is not published.
OpenAI Containers: You pick a monthly plan from $20, and all of it becomes usage credit spent per second on running sandboxes. A stopped sandbox costs nothing and keeps its disk.
Limits in those scenarios
Daytona limits the total vCPU, memory and disk running at once, up to 500 vCPU on Tier 4, so 300 user sandboxes (600 vCPU) and 1,000 short jobs at once (2,000 vCPU) need a custom limit; it also caps one sandbox at 4 vCPU / 8 GiB by default. OpenAI Containers fit none of the five scenarios as written: no persistent disk, no Docker, no internet for Code Interpreter and Hosted Shell, and no published machine size or concurrency limit. On boat only the 1,000-job burst does not fit: starts per minute and per day are capped, so those starts are queued.
| Scenario | Daytona | OpenAI Containers | boat |
|---|---|---|---|
| One coding agent, workdays |
|
| None that bite |
| One agent that never stops |
|
| None that bite |
| 50 agents in parallel |
|
| None that bite |
| Sandboxes for your users |
|
| None that bite |
| 1,000 short jobs at once |
|
|
|
Which one should you use?
Use Daytona when
you need sandboxes you keep and reach from outside, built from your own Docker images, or need GPUs, Windows or US regions.
- A sandbox you keep and can reach. Useful for agents that work for days: Daytona sandboxes keep their disk, have no session cap and take SSH and preview URLs.
- GPUs and Windows. Useful if your agents test models or need Windows: Daytona rents Nvidia and AMD GPUs and runs Windows VM sandboxes.
- Your own images, pause with memory. Daytona builds sandboxes from Docker images, and its VM classes pause and fork with memory kept.
Use OpenAI Containers when
your app already calls OpenAI models and the model only needs to run short pieces of code or shell commands on files you give it.
- Built into the model call. Useful if your app already calls OpenAI models: one tool line in a request gives the model a place to run code.
- Locked-down network by default. Useful if code must only reach chosen hosts: Code Interpreter and Hosted Shell have no outbound access until an admin allows domains.
- No plan or wallet. Useful for light use: each container session is billed by the minute with your tokens, with no top-up and nothing to clean up.
Where boat fits
If what you are really running is coding agents that install, build, test and serve apps for hours, look at boat. Every sandbox is a full VM with root, Docker and a disk that stays, with open internet, reachable ports and coding agents built in. It also ran faster than Daytona in the same CPU test, and OpenAI Containers were not measured.
A full VM with root, Docker and /dev/kvm
Daytona's default sandbox is a container on a shared host kernel; its VM class needs KVM turned on for your organization. OpenAI runs commands without sudo and documents no Docker, so apt installs and emulators stop there.
A disk that stays through every stop
An OpenAI container discards its files after 20 idle minutes, so your code re-uploads the repo each time. Daytona keeps the disk but bills it while stopped. boat saves the disk every minute and a stopped sandbox costs nothing.
Open internet and ports from the start
Daytona's Tier 1 and 2 reach only an allowlist until a $500 top-up, and OpenAI's Code Interpreter starts offline with no inbound access. boat has open internet on every plan, HTTPS on 50 ports and raw TCP.
Use boat when your agents do real work for hours: root, Docker and /dev/kvm on a full, faster VM, a disk that stays, open internet, reachable ports and coding agents built in. Compare it one to one: boat vs Daytona and boat vs OpenAI Containers.
Questions people ask
Is Daytona cheaper than OpenAI Containers?
In most scenarios we priced, yes: one coding agent on workdays comes to $56 a month on Daytona and $228 on OpenAI, and 50 agents in parallel come to $2,682 versus $11,405. For sandboxes for your users OpenAI is lower, $1,620 against $2,000, though neither fits. OpenAI also bills model tokens on top; boat comes to $20, $317 and $200 for those three.
Which is faster, Daytona or OpenAI Containers?
Only Daytona has a measured number: its Linux VM class did 21.52 runs per second in the public Node.js build-and-test benchmark at 4 vCPU / 8 GB. OpenAI Containers were not tested and their vCPU is not published. boat did 26.69 in the same run.
Can Daytona or OpenAI Containers run Docker?
Daytona runs Docker in all its sandbox classes, and /dev/kvm on its Linux VM class once KVM is turned on for your organization. OpenAI's hosted shell runs commands without sudo, and no Docker support is documented. boat has root, systemd, Docker and /dev/kvm on every sandbox.
How long does a sandbox last on each?
A Daytona sandbox has no session cap by default and keeps its disk when stopped. An OpenAI container expires after 20 minutes without use, and its data is discarded and cannot be recovered. A boat sandbox has no session cap on paid plans and keeps its disk when it stops.
Can the sandboxes reach the internet?
Daytona's Tier 1 and Tier 2 reach only package registries, git hosts and AI APIs; open internet starts at Tier 3, after a $500 top-up. OpenAI's Code Interpreter and Hosted Shell containers have no outbound access until an admin adds domains to an org allowlist. boat sandboxes have open internet on every plan.
Where does my data run?
Daytona offers US and EU regions, plus dedicated regions and your own machines. OpenAI's Code Interpreter can process data in the US or Europe, while the Agents API supports data residency only in the US. boat runs only in the EU, in Germany, Finland and France.
Try boat
Install the CLI, then run boat new.
7-day free trial