Best Daytona.io Alternatives for AI Agent Sandboxes

The best Daytona alternatives for AI agents are E2B for open-source microVMs that pause and fork with memory, Modal for GPU sandboxes on gVisor, and Beam for GPU sandboxes plus persistent microVMs. Fly.io Sprites, Tensorlake, Northflank and Microsandbox cover narrower needs. Daytona.io leads on Windows and macOS desktops, so this guide shows where each option beats Daytona and where it falls short.

Why teams look for Daytona alternatives

Four things push teams to look past Daytona: its core development moved to a private codebase and the public repository is archived, pause and fork only work on VM classes, GPU sandboxes are deleted when they stop, and Linux sandboxes have tight size limits. Daytona does sell GPU, Windows and macOS sandboxes, so a lack of GPUs is not a reason to switch.

Daytona's open-source repository is archived

Daytona moved its core development to a private codebase. The daytonaio/daytona repository is archived, and its README says it will get no further updates, fixes or releases. The last public release, v0.190.0, stays usable under AGPL-3.0, but Daytona doesn't patch it.

Teams that picked Daytona so they could self-host need a new plan. Daytona's Bring Your Own Compute option attaches your own runner nodes, but Daytona's control plane still manages them, and BYOC has to be enabled for your organization.

Containers by default, VMs for memory

Daytona sandboxes run as Linux containers unless you choose a VM class. Pause and resume, fork, and memory snapshots work only on the Linux VM and Windows classes, according to Daytona's sandbox docs. A container sandbox keeps its filesystem when it stops, but its memory is gone. If your agent needs to pick up mid-process, you run on a VM class, using one of Daytona's default VM snapshots or your own.

GPU sandboxes are ephemeral

Daytona sells GPU sandboxes from the NVIDIA RTX 4090 up to the B300, plus the AMD MI355X. Each one is a Linux container with exclusive GPUs, and Daytona deletes it when it stops, so GPU work can't pause or fork.

On Daytona's pricing page, an on-demand RTX 4090 costs $0.99 per hour and an H100 costs $3.95. Preemptible capacity is cheaper at $0.57 and $2.27, but Daytona can reclaim a spot sandbox without notice.

Size limits on Linux sandboxes

Daytona's docs cap each sandbox in an organization at 4 vCPU, 8 GB of RAM and 10 GB of disk, and a new sandbox gets 1 vCPU, 1 GB and 3 GiB unless you ask for more. Windows snapshots go up to 16 GiB of RAM, and GPU sandboxes scale higher. For Linux work, that ceiling is tight for large builds or a full browser desktop inside one sandbox.

Where Daytona is the better choice

Daytona is the strongest pick for Windows and macOS. Its Computer Use API drives Linux and Windows desktops, Windows sandboxes run their own Windows kernel, and macOS sandboxes run on reserved Apple silicon through use.computer. Daytona also ships SDKs for Python, TypeScript, Ruby, Go and Java. At $0.0504 per vCPU-hour, its CPU rate matches E2B's and undercuts Beam and Modal sandboxes.

Daytona alternatives compared

E2B keeps memory through pause and fork on every sandbox, and Tensorlake does on named sandboxes. Beam sandboxes, Modal and Northflank attach GPUs, Northflank and Beam VMs have the lowest CPU rates, and only Daytona covers Windows and macOS. "Not documented" means the vendor's docs don't say, and CPU prices exclude memory, storage and plan fees.

For a 4 vCPU, 8 GiB environment running one hour, CPU plus RAM comes to about $0.33 on Daytona and E2B, $0.45 on a Beam sandbox and $0.48 on Modal. A Beam VM of the same size is about $0.14 and Northflank is $0.13. Sprites and Tensorlake bill only the CPU you actually use, so a mostly idle agent costs less there.

The best Daytona alternatives for AI agents

For AI agents, E2B is the best fit for CPU sandboxes that pause and fork with memory, Beam for GPU sandboxes plus persistent microVMs, and Modal for GPU sandboxes next to models already on Modal. Tensorlake, Fly.io Sprites, Northflank, Microsandbox and Nightona fit narrower needs, and none of them replaces Daytona's Windows and macOS sandboxes.

Beam: GPU sandboxes and persistent microVMs

Beam has two products that map onto Daytona's split between containers and VMs. Beam sandboxes are isolated containers for short-lived code execution, with GPU support. Beam virtual machines are persistent CPU microVMs, each with its own kernel.

Sandboxes boot in seconds, bill by the millisecond while running, and take a GPU with one argument, such as gpu="RTX4090". Python and TypeScript SDKs both support them. On supported runtimes, a sandbox can snapshot its memory, running processes included, and restore that snapshot into several new sandboxes. Daytona allows this only on its VM classes. This example from Beam's sandbox quickstart forks a running web server three times:

from beam import Sandbox


sb = Sandbox(cpu=1, memory="1Gi", keep_warm_seconds=600).create()
print(sb.process.run_code("print(sum(range(10)))").stdout)  # 45

# Start a web server and get a URL
sb.fs.write_text("/workspace/index.html", "Hello from a Beam sandbox")
sb.process.exec(
    "python3", "-m", "http.server", "8000", "--bind", "0.0.0.0",
    cwd="/workspace",
)
print(sb.expose_port(8000))

# Snapshot memory, including the running server, then fork it
snapshot_id = sb.snapshot_memory()
sb.terminate()

forks = [Sandbox().create_from_memory_snapshot(snapshot_id) for _ in range(3)]
for fork in forks:
    print(fork.list_urls())  # each fork serves its own copy
    fork.terminate()

Sandbox preview URLs are public, so put authentication in the app you serve. Daytona's previews require a token by default.

VMs handle the persistent side. Pause keeps RAM and running processes, and stop keeps the disk. The VM docs also cover fork, filesystem snapshots, SSH, a browser terminal, Docker and systemd. A VM can run an Ubuntu desktop with a screenshot, click and type API for computer-use agents. An idle timeout can pause the VM and wake it on the next request:

beam vm new devbox
beam vm ssh devbox
beam vm update devbox --ttl 300 --idle-action pause --auto-resume

VMs cost $0.0252 per vCPU-hour plus $0.0054 per GiB-hour, billed per second, and stopped or paused VMs release their compute. The default 4 CPU, 8 GiB VM works out to about $0.14 an hour (4 × $0.0252 + 8 × $0.0054).

Beam's runtime, beta9, is open source under AGPL-3.0. It ships runc, gVisor and microVM runtimes, and its default worker configuration uses gVisor. You can self-host it, but it doesn't include everything Beam Cloud offers, and the self-hosting guides don't cover VMs. BYOC runs Beam workloads in your own AWS, GCP or Azure account.

Beam falls short on operating systems and sandbox price. It has no Windows or macOS option, VMs are CPU-only, and sandbox CPU costs more than Daytona's ($0.0675 against $0.0504 per vCPU-hour). Pick Beam if you want GPU sandboxes and persistent agent VMs in one account, backed by an open-source runtime.

E2B: open-source microVMs that pause and fork

E2B runs every sandbox in a microVM built on Firecracker, with a dedicated kernel. Pause, snapshots and fork all keep memory, on every sandbox. E2B's persistence docs say a paused sandbox is kept until you kill it, and its pricing FAQ says paused sandboxes aren't billed.

E2B publishes its stack under Apache-2.0, and E2B Embed runs all of it on infrastructure you control, from a single Linux host to your own cloud account. BYOC on AWS, GCP and Azure is an Enterprise option. Its CPU and memory rates match Daytona's to the cent, and our breakdown of E2B pricing walks through the plans.

The trade-offs are GPUs and session length. E2B sandboxes are CPU-only, and continuous runtime is capped at 1 hour on Hobby and 24 hours on Pro, which costs $150 a month. The cap resets when you pause and resume. Pick E2B if you want memory pause and fork on every sandbox with a self-hostable stack, and you don't need GPUs. Our guide to E2B alternatives covers the options if E2B itself doesn't fit, including Vercel Sandbox and Cloudflare Sandboxes.

Modal: GPU sandboxes on gVisor

Modal Sandboxes run on gVisor or on a VM runtime with its own Linux kernel. GPU sandboxes work only on gVisor. If your models already run on Modal, sandboxes sit in the same account and SDK.

Limits are tighter than Daytona's. A sandbox lives 5 minutes by default and 24 hours at most, and it can't pause. Filesystem snapshots expire after 30 days unless you change the TTL. Memory snapshots carry an alpha label: each one expires after 7 days, taking one ends the sandbox, and they don't work with GPU sandboxes.

Modal bills sandboxes at three times its list price: $0.00003942 per core-second, where a core is 2 vCPU. That's about $0.071 per vCPU-hour. Pick Modal for GPU code execution that finishes within a day.

Fly.io Sprites: persistent Linux computers

Sprites are persistent Linux VMs from Fly.io, each with a 100 GB disk and its own URL that wakes it on request. An idle Sprite goes warm first, with memory frozen and a 100 to 500 ms resume. Later it goes cold, memory is dropped, and the next wake takes 1 to 2 seconds. The switch is automatic, so long-lived processes should run as Sprite services that restart on wake.

Billing counts the CPU you use ($0.0385 per CPU-hour) and the memory you use ($0.021875 per GB-hour). Warm and cold Sprites cost nothing for compute. The trade-offs: every Sprite gets the same 8 vCPU and Fly.io's resource list includes no GPU, checkpoints cover only the filesystem, and SSH needs a server you install yourself. Pick Sprites for agent workspaces that sit idle most of the day.

Tensorlake: Firecracker sandboxes with memory clones

Tensorlake runs each CPU sandbox in a Firecracker microVM, and GPU sandboxes, available by request, run on gVisor. Named sandboxes suspend and resume with memory, filesystem and processes intact. A clone restores memory and running processes into one or more new sandboxes. Tensorlake also offers SSH, an Ubuntu VNC image for computer use, and BYOC in your own cloud account on the Enterprise plan.

The pricing page lists no GPU rate. On usage credits, CPU costs $0.07 per active core-hour and RAM $0.015 per GB-hour, and the $250-a-month Pro plan lowers both rates. A suspended sandbox is billed as snapshot storage. The free tier runs one sandbox at a time with 1 vCPU and 2-hour sessions. Pick Tensorlake if you want what Daytona reserves for VM classes on every named sandbox, and can wait for GPU access.

Northflank: microVM sandboxes inside a full platform

Northflank runs sandboxes as microVMs on Cloud Hypervisor, each with a dedicated guest kernel, and uses gVisor for GPU sandboxes. It's a full platform, so services, jobs and managed databases sit next to the sandboxes. BYOC covers AWS, Google Cloud, Azure, Oracle and bare metal, and the enterprise tier can run the control plane air-gapped.

Northflank has the lowest CPU rate in this list: $0.01667 per vCPU-hour, plus $0.00833 per GB-hour of memory. On-demand GPUs run from the L4 to the B200. Pausing a sandbox scales it to zero, which stops compute billing, but running processes and anything outside an attached volume are lost. Pick Northflank if you want sandboxes and the rest of your stack on one platform in your own cloud.

Microsandbox: local microVMs you run yourself

Microsandbox is an Apache-2.0 library and CLI that starts microVMs on your own machines. It runs on macOS (Apple silicon), Linux (KVM) and Windows (Windows Hypervisor Platform) hosts. It runs standard OCI images, can fork live sandboxes or save their state, and its README reports average boot times under 100 ms.

It's beta software with no managed service, so you operate the hosts. Pick Microsandbox to embed sandboxes in your own product or CI without a vendor.

Nightona: the community fork of Daytona

Nightona is a community fork of Daytona's last open release, v0.190.0, under AGPL-3.0, and it isn't affiliated with Daytona. The code is functionally the same as v0.190.0, and Nightona-branded packages and container images are not published. Pick Nightona if you already self-host Daytona and want to stay on that codebase.

How to choose a Daytona alternative

Start from the Daytona feature you depend on most, then pick the alternative that covers it. For most teams that's open source, GPUs, memory persistence, a desktop or price.

• You self-hosted Daytona. E2B publishes its runtime and control plane under Apache-2.0, and E2B Embed runs the stack on infrastructure you control. Beam's beta9 covers sandboxes, GPU inference and background jobs under AGPL-3.0. Microsandbox fits embedding microVMs in your own product, and Nightona keeps the old Daytona code going. Our walkthrough on self-hosting a code sandbox covers the setup work.
• You need GPUs. Beam sandboxes attach a GPU such as an RTX 4090 with one argument. Modal, Northflank and Tensorlake (by request) run GPU sandboxes on gVisor.
• You need memory to survive a pause. E2B keeps memory across pause and fork on every sandbox, and Tensorlake does on named sandboxes. Beam VMs keep RAM and processes on pause, and Beam sandboxes fork from memory snapshots. Our comparison of stateful sandboxes goes deeper on what each state keeps.
• You need a desktop for computer use. Beam VMs, E2B and Tensorlake offer Linux desktops, and so does Daytona. For Windows or macOS, Daytona is the only option in this guide.
• You care most about price. Northflank has the lowest CPU rate. Beam VMs cost $0.0252 per vCPU-hour and nothing for compute while paused or stopped. Sprites bill only the CPU and memory a Sprite actually uses.

FAQ

What is Daytona.io?

Daytona.io is a hosted platform for running AI-generated code in sandboxes. It offers Linux containers by default, plus Linux VM, Windows and GPU sandboxes, with SDKs for Python, TypeScript, Ruby, Go and Java, and macOS sandboxes through use.computer. Its core code is developed in a private codebase.

What is the best Daytona.io alternative?

E2B is the closest match for CPU sandboxes that pause and fork with memory. If you use Daytona's GPU sandboxes or keep long-running agent machines, Beam covers both with GPU sandboxes and persistent microVMs. For Windows or macOS sandboxes, no alternative in this guide replaces Daytona.

Which Daytona alternatives work best for AI agents?

Agents that run short code snippets fit E2B, Modal or Beam sandboxes. Agents that keep a workspace for days fit Beam VMs, E2B, Fly.io Sprites or Tensorlake named sandboxes, since those keep their disk between sessions. Beam VMs, E2B and Tensorlake keep memory through a pause, while Sprites keep it only while warm.

Is Daytona still open source?

Not for new development. Daytona moved its core to a private codebase and archived the public repository, so it gets no more updates. The last release, v0.190.0, remains available under AGPL-3.0, and the community fork Nightona continues it.

Which Daytona alternatives support GPUs?

Beam, Modal and Northflank offer GPU sandboxes, and Tensorlake offers them by request. E2B and Beam VMs are CPU-only, and Fly.io lists no GPU for Sprites. Daytona itself offers eight GPU models: seven NVIDIA GPUs from the RTX 4090 to the B300, plus AMD's MI355X.

Can any alternative run Windows or macOS sandboxes?

None of the alternatives in this guide do. Daytona offers Windows sandboxes, and macOS sandboxes through use.computer, while Beam VMs, E2B and Tensorlake provide Linux desktops. If your agent has to drive Windows or macOS apps, Daytona is the practical choice.