Fly.io Machines vs GitHub Codespaces

Fly.io Machines are fast microVMs you boot from your own image to host apps near users, and they run until you stop them. GitHub Codespaces are ready dev containers opened from a repository in VS Code, and each one stops after 12 hours at most.

The companies and products

Fly.io Machines

Fly.io is an app hosting platform, and Machines are the microVMs underneath it that you can also start and stop through a REST API.

A Fly Machine boots your Docker image as a Firecracker microVM on Fly's own servers, in one of 17 regions. You pick a shared or performance CPU preset, attach at most one Volume for data that must last, and Fly Proxy can stop, suspend and wake Machines as traffic comes and goes. It is built for teams that host web apps and services worldwide; it is not a sandbox product, so this page compares the parts that overlap with agent work.

Kind of product: App hosting platform; Machines are its VM building block with a REST API
Isolation: Firecracker microVMs with hardware virtualization, on Fly's own servers
Regions: 17 regions in North America, Europe, Asia, Oceania, South America and Africa
CPU classes: Shared vCPUs guarantee 6.25% of each core with a burst balance; performance vCPUs get the full core
Storage: Root file system is ephemeral; one Volume of up to 500GB per Machine for lasting data
Free trial: 2 Machine hours or 7 days, up to 10 Machines of 2 vCPU / 4GB that stop after 5 minutes
Compliance: Lists SOC 2 Type II; a HIPAA package with a pre-signed BAA is sold as an add-on

GitHub Codespaces

GitHub Codespaces is GitHub's cloud development environment: a ready-to-code Linux machine for a repository, opened in the browser, VS Code or the GitHub CLI.

Codespaces is a different kind of product from boat: a dev environment for people working on a GitHub repository, not a sandbox API for agents. Each codespace is a Docker container built from the repo's dev container config, running on its own newly built VM on Azure, with 2 to 32 cores. It is built for developers and teams who want every contributor to start from the same setup, with prebuilds, port forwarding and GitHub billing.

Isolation: A Docker container on its own newly built VM, with its own virtual network
Operating system: Linux only; Windows and macOS are not supported for the remote container
Machine sizes: 2, 4, 8, 16 or 32 cores, with 4 GB of memory per core
Lifetime: Stops after 30 idle minutes by default (5 to 240), and after 12 hours at most even while in use
Regions: US East, US West, Europe West and Southeast Asia
Free usage: Personal Free accounts get 120 core-hours and 15 GB-month a month, Pro 180 and 20; organizations get no free quota
Compliance: GitHub Enterprise Cloud lists SOC 1, SOC 2 and SOC 3 reports and ISO 27001

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. “92nd cheapest of 367” means 91 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	Fly.io Machines: price rank	GitHub Codespaces: price rank	boat: price rank
Software factory 100 at once · 4 vCPU / 8 GB · 2,200 sessions of 8 h a month Neither fits fully: Fly needs a Volume for files that must last and offers no /dev/kvm, while Codespaces stops every 12 hours; boat fits with Docker, /dev/kvm and a kept disk.	92nd of 367, with limits $836 a month	274th of 367, with limits $4,618 a month	3rd cheapest of 367 $634 a month
Always-on AI employees 50 machines 24/7 · 2 vCPU / 4 GB Fly Machines run until stopped, which suits a long-lived assistant better than Codespaces and its 12-hour cap, though Fly keeps only what sits on the one Volume.	125th of 366, with limits $816 a month	309th of 366, with limits $6,970 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 Fly fits short bursts best of the three on paper, with per-second billing and no plan fee, while each codespace builds a dev container on a new VM first.	75th of 345, with limits $94 a month	288th of 345, with limits $619 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 Fly can host one Machine per user through its API, while Codespaces are made for GitHub users on a repository and GitHub does not publish how many can run at once.	69th of 361, with limits $600 a month	281st of 361, with limits $1,964 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	48th of 360, with limits $2,838 a month	282nd of 360, with limits $9,489 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	117th of 364, with limits $457 a month	295th of 364, with limits $1,519 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 Busy CI jobs drain a shared Fly vCPU's burst balance, and Codespaces has no fork or snapshot API, so each run starts from a repo or prebuild.	152nd of 377, with limits $288 a month	314th of 377, with limits $909 a month	4th cheapest of 377 $86 a month
24/7 dev boxes 1 machine 24/7 · 4 vCPU / 8 GB Codespaces gives a polished VS Code box per repo but stops after 12 hours; Fly runs 24/7 but you build the image; boat is a full VM that keeps running.	118th of 368, with limits $53 a month	130th of 368, with limits $270 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 Neither ships a graphical desktop, so computer-use agents need one built by hand on both, while boat streams a 60fps desktop with Chromium.	95th of 369, with limits $173 a month	267th of 369, with limits $1,367 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	160th of 367, with limits $90 a month	275th of 367, with limits $678 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	161st of 346, with limits $67 a month	310th of 346, with limits $922 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 Fly is the strongest of the three here, since it can spread scrapers across 17 regions and bill only the seconds they run.	44th of 338, with limits $1,232 a month	280th of 338, with limits $18,637 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	118th of 360, with limits $63 a month	267th of 360, with limits $445 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	Can't run it	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	Fly.io Machines	GitHub Codespaces	boat
Kind of product	App hosting platform; you boot your own image as a microVM	Cloud dev environment: a dev container per GitHub repository	Agent sandbox: a full VM per agent, ready to use
Isolation	Firecracker microVM with its own kernel	A Docker container on its own newly built VM	Full VM with its own kernel on dedicated AMD Ryzen 9 9950X (Zen 5) hosts
How long it runs	Runs until you or Fly Proxy stop it; no documented maximum	Stops after 30 idle minutes by default and after 12 hours at most, even while in use	Runs until you stop it; no session cap on paid plans
Docker, systemd and nested virtualization	Root and Docker you install yourself; no systemd; /dev/kvm not offered	Docker and sudo inside the dev container; /dev/kvm not documented	Docker, root, systemd and /dev/kvm on every machine
Files after a stop	Root file system is ephemeral; lasting data goes on one Volume, billed for its full size around the clock	Saved files are kept and storage is billed; stopped codespaces are deleted after 30 days by default	The whole disk is kept, with snapshots every minute and on stop; a stopped sandbox costs nothing
Pause with memory	Suspend keeps memory for Machines up to 2GB	No memory state is kept; processes end at each stop	Resume reboots from disk (no memory snapshots)
Fork and copies	Clone copies a Machine's config; a cloned Volume starts empty	No copy or snapshot endpoint; new codespaces start from a repo, branch or prebuild	Fork a running sandbox, disk included; named snapshots as templates
Starting point	Any Docker image you build	Dev container config in the repo, with prebuilds built by GitHub Actions	Named snapshots (templates), shareable by code; no Dockerfile builds
Desktop and computer use	None built in; you add a desktop and browser to your image	VS Code, JupyterLab and a terminal; no graphical desktop	60fps desktop and Chromium, computer use and browser control, embeddable stream
Coding agents	None built in; you install and run agents yourself	GitHub Copilot as a VS Code extension; other agents you install yourself	Claude Code, Codex, OpenCode and more preinstalled, with a prompt, steer and events API
Keeping keys out of the sandbox	Secrets arrive as environment variables; an open-source tokenizer proxy you deploy yourself	Secrets are copied into the codespace as environment variables	AI credentials proxy for model providers and any HTTPS API; switch a credential to another account when credits run out
Reaching the machine	Public HTTPS and TCP through Fly Proxy, Anycast IPs, custom domains, private network	A URL per forwarded port and SSH tunnels; no public IP	HTTPS URLs for up to 50 ports, token-protected; raw TCP; dedicated IPv6 or IPv4
Outbound rules	Network policies allow chosen ports and protocols and deny the rest	Open internet; GitHub says there is no way to restrict it	Open internet on every plan; no provider-side allowlist
Regions	17 regions on six continents	US East, US West, Europe West and Southeast Asia	EU only: Germany, Finland, France

Every feature Battleships tracks (43)

Feature	Fly.io Machines	GitHub Codespaces	boat
Full VM (own kernel)	Yes	Yes	Yes
Docker inside	Yes	Yes	Yes
Nested virtualization	No	No	Yes
Root	Yes	Yes	Yes
Systemd	No	Not published	Yes
Desktop GUI	No	No	Yes
Browser	No	No	Yes
Computer-use API	No	No	Yes
SSH	Yes	Yes	Yes
Persistent disk	Yes	Yes	Yes
Pause/resume	Yes	Yes	Yes
Automatic snapshots	Yes	No	Yes
Fork/clone	Yes	No	Yes
Live fork (no pause)	Yes	No	Yes
Memory fork	No	No	No
Custom image (Docker or snapshot)	Yes	Yes	Yes
≥24 h sessions	Yes	No	Yes
Idle auto-stop	Yes	Yes	No
Wake on request	Yes	No	No
HTTPS preview URLs	Yes	Yes	Yes
Raw TCP inbound	Yes	No	Yes
Public IPv4	Yes	No	No
Egress allowlist	Yes	No	No
Secret proxy	No	No	Yes
Secret proxy for any API	No	No	Yes
Preinstalled agents	No	No	Yes
Agent harness API	No	No	Yes
MCP server	Yes	No	No
GPU	No	No	No
Windows	No	No	No
Arm64	No	No	No
Self-hosting	No	No	No
BYOC	No	No	No
Open source	Yes	No	No
Scoped API keys	Not published	Not published	Yes
Spend limits	No	Yes	Yes
Usage per sandbox (API)	No	No	Yes
Audit logs	Not published	Yes	No
SSO	No	Yes	No
SOC 2	Yes	Yes	No
HIPAA	Yes	No	No
EU data residency	Yes	Yes	Yes
Zero data retention	Not published	Not published	Yes

Performance

Fly.io MachinesNot measured

GitHub CodespacesNot measured

boat26.69 runs/s

There is no comparable measurement for either one: neither Fly.io Machines nor GitHub Codespaces was in the public StarSling run where boat did 26.69 Node.js build-and-test runs per second at 4 vCPU / 8 GB. Fly's shared vCPUs guarantee only 6.25% of each core with a burst balance, so its results would depend on whether you pick shared or performance CPUs.

Node.js build-and-test loop at 4 vCPU / 8 GB, higher is better. Measured with the open hpc-sandbox-benchmarks suite. Fly.io Machines and GitHub Codespaces have 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	Fly.io Machines, a month	GitHub Codespaces, 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	$15 · Pay As You Go · with limits	$51 · Personal account: GitHub Free	$20 · $20/mo
One agent that never stops 4 vCPU / 8 GB, 50 GB disk, running 24/7 all month	$36 · Pay As You Go · with limits	$270 · Personal account: GitHub Free · 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	$487 · Pay As You Go · with limits	$3,019 · Personal account: GitHub Free	$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	$110 · Pay As You Go · with limits	$850 · Personal account: GitHub Free · 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	$232 · Pay As You Go · with limits	$1,889 · Personal account: GitHub Free · with limits	$2,000 · $2000/mo · with limits

Fly.io Machines: Fly bills each Machine per second while it runs, by CPU preset and memory, with no plan fee; Volumes are billed for their full size all month. The figures here use shared vCPUs bought in 1-year reservation blocks, Fly's lowest rate.

GitHub Codespaces: Codespaces bills $0.09 per core-hour while a codespace is active, plus $0.07 per GB-month of storage while it exists. A 4 vCPU / 8 GB job is priced on the 4-core 16 GB machine, and personal accounts get a free monthly quota.

GitHub Codespaces: 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

Fly shows as a compromise in every scenario because its lowest figures need a 1-year reservation and use shared vCPUs that are throttled above 6.25% of each core, so long builds and tests slow down. Codespaces stops every codespace after 12 hours, so it does not fit the always-on agent, and GitHub does not publish how many can run at once, so 300 user sandboxes and 1,000 short jobs are not confirmed. On boat the 1,000-job burst is limited by starts per minute and per day, so it gets queued even on the $2,000 plan.

Scenario	Fly.io Machines	GitHub Codespaces	boat
One coding agent, workdays	different kind of product: app platform 1-year commitment burstable CPU: 6.25% of each vCPU guaranteed, throttled above that	None that bite	None that bite
One agent that never stops	different kind of product: app platform 1-year commitment burstable CPU: 6.25% of each vCPU guaranteed, throttled above that	Personal account: GitHub Free: sessions capped at 12 h	None that bite
50 agents in parallel	different kind of product: app platform 1-year commitment burstable CPU: 6.25% of each vCPU guaranteed, throttled above that	how many machines can run at once: limit not published, probably fine at 50 (the typical published limit is 50)	None that bite
Sandboxes for your users	different kind of product: app platform 1-year commitment burstable CPU: 6.25% of each vCPU guaranteed, throttled above that	not confirmed: how many machines can run at once (you need 300; the typical published limit is 50)	None that bite
1,000 short jobs at once	different kind of product: app platform 1-year commitment burstable CPU: 6.25% of each vCPU guaranteed, throttled above that	not confirmed: how many machines can run at once (you need 1,000; the typical published limit is 50)	max 2,400 starts/day (needs ~6,667) max 600 starts/hour (needs ~1,000) bursts above 90 starts/min are queued (a burst of 333 takes ~4 min to start)

Which one should you use?

Use Fly.io Machines when

you host web apps or services that must run near users around the world, sleep between requests and wake on traffic.

No time limit. Useful for services and long jobs: a Fly Machine runs until you stop it, while a codespace stops after 12 hours.
17 regions and wake on request. Useful for apps near users worldwide: Fly runs in 17 regions and Fly Proxy wakes a sleeping Machine when traffic arrives.
Public endpoints and egress rules. Useful if you host a product: Fly gives public HTTPS and TCP, custom domains and port-level outbound rules.

Use GitHub Codespaces when

your developers want a ready VS Code environment for a GitHub repository, opened from a branch or pull request.

Built into GitHub. Useful if your team lives on GitHub: open a ready codespace from any repo, branch or pull request.
A ready editor. Useful for people, not just code: VS Code in the browser or on your machine, with dev containers and prebuilds set up.
Free hours for personal accounts. Useful for occasional personal work: a GitHub Free account includes 120 core-hours and 15 GB-month each month.

Where boat fits

Fly.io Machines are built for hosting apps and GitHub Codespaces for developers working in a repository, so teams using either for agents end up building the sandbox around them. If what you are really running is agents that install, build, test and browse for hours, boat gives each one a full VM with the disk, desktop and agent controls already in place.

A disk that keeps everything, with no time limit

A Fly Machine loses anything outside its one Volume on restart, and a codespace stops at 12 hours with its processes ended. boat runs until you stop it, saves the disk every minute and on stop, and a stopped machine costs nothing.

/dev/kvm, systemd and a desktop

Neither Fly nor Codespaces offers /dev/kvm or a graphical desktop, so emulators, nested VMs and computer-use agents need workarounds or do not run. Every boat machine has Docker, systemd, /dev/kvm and a 60fps desktop with Chromium.

Agents driven from outside, keys kept out

On both you install agents yourself, write the code that prompts and watches them, and pass keys in as environment variables that agent code can read. boat preinstalls coding agents with a prompt, steer and events API, and its credentials proxy keeps real keys outside.

Use boat when your agents do real work for hours or days: full VMs with /dev/kvm, Docker and a desktop, a disk that survives every stop, forks of running machines, and coding agents with keys kept outside. Compare it one to one: boat vs Fly.io Machines and boat vs GitHub Codespaces.

Questions people ask

Is Fly.io Machines cheaper than GitHub Codespaces?

In every scenario we priced, yes, using Fly's lowest rate of shared vCPUs on a 1-year reservation. One agent running all month is $36 on Fly against $270 on Codespaces, and 50 agents in parallel are $487 against $3,019. boat comes to $26 and $317 for the same two, with full cores and no reservation.

Which is faster, Fly.io Machines or GitHub Codespaces?

Neither has a comparable public measurement. Fly's shared vCPUs guarantee 6.25% of each core and get throttled under steady load, while its performance vCPUs get the full core. boat did 26.69 Node.js build-and-test runs per second at 4 vCPU / 8 GB in StarSling's benchmark.

Can I run an AI agent 24/7 on either one?

On Fly yes, since a Machine runs until you stop it, though only its Volume keeps files across restarts. A codespace stops after 12 hours at most, even while in use, so 24/7 work needs a restart script. A boat sandbox runs until you stop it and keeps its whole disk.

Can Fly.io Machines and GitHub Codespaces run Docker?

Both can: on Fly you install Docker inside the microVM yourself, and Codespaces runs Docker inside the dev container. Neither offers /dev/kvm, so Android emulators and nested VMs are not available. boat has Docker, systemd and /dev/kvm on every machine.

Where do they run?

Fly runs Machines in 17 regions on six continents, and Codespaces in US East, US West, Europe West and Southeast Asia. boat runs only in the EU, in Germany, Finland and France, with EU data residency.

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