Table of Contents
- Why teams look for a Daytona alternative
- The 8 best Daytona alternatives in 2026
- Daytona alternative pricing: one workload, checked October 12, 2026
- Agent37 vs Daytona: the direct comparison
- If you ran the open-source Daytona dev environment manager
- How to choose
- FAQ
- What is the cheapest Daytona alternative?
- Is Daytona still open source?
- Can you self-host Daytona?
- Does Daytona run VMs or containers?
- Which Daytona alternatives offer GPUs?
Do not index
The best Daytona alternative depends on why you are leaving. For sandboxes that accumulate real running time, Agent37 (our product) prices the same 2 vCPU, 4 GB workload at $4.76 for a 730-hour month, where Daytona's published rates work out to $120.89. If the June 2026 closed-sourcing is what moved you, the options are a platform that still names its stack, or forking Daytona's final AGPL release yourself. And to be precise about which Daytona: this guide covers daytona.io, the sandbox platform for running AI-generated code, not the watch or the race car.
We checked every price in this guide against each provider's own pricing page on October 12, 2026. That matters more than usual here, because the pages currently ranking for Daytona alternatives contradict each other and the product. Several still call Daytona open source (that ended in June 2026), and several claim it lacks GPU support (its pricing page lists eight GPU types). This guide states its date, shows the monthly math, and corrects the stale claims as it goes.
Why teams look for a Daytona alternative
Daytona earned its place in the sandbox market honestly. Sandbox creation runs under 90 milliseconds, billing is per second with no subscription fee, SDKs ship for Python, TypeScript, Ruby, Go, and Java, and sandbox classes cover Linux containers, Linux and Windows VMs, macOS desktops, and GPUs. New accounts get $200 in free compute, and its February 2026 Series A announcement names LangChain, Writer, and Turing as customers. Teams leave anyway, for four documented reasons.
First, the open-source story ended. Daytona launched in March 2024 as "genuinely open source under the Apache 2.0 license", and the launch post leaned on the fork-it-if-we-go-wrong guarantee. The April 2025 pivot to AI sandboxes relicensed the repo to AGPL-3.0, and on June 11, 2026 the company announced it was going closed source, citing one reason: "AI can now be pointed at an open source repository and systematically search it for exploitable flaws." The final open release, v0.190.0, landed June 23, 2026; the same day, the repository's main branch was replaced with a maintenance notice, and on October 3, 2026 the 71.6k-star repo was archived read-only. One founder on r/AI_Agents in September 2026: "initially we were using Daytona's sandboxes, but they recently closed-sourced them... we recently switched to building our own sandbox using Docker." None of that makes Daytona a bad product, but if you adopted it partly because you could fork it, that reason is gone.
Second, the tier ladder gates real work. The $200 credit is real, but Tier 1 (verified email) caps your whole organization at 10 vCPU, and network access on Tiers 1 and 2 "is restricted and cannot be overridden at the sandbox level." Full internet access starts at Tier 3, which requires a $500 top-up. One Hacker News commenter put it plainly in October 2026 (on our own launch thread, so weigh the venue): "Got a bunch of Daytona credits which are close to useless given their restrictions until you hit tier 3."
Third, the compute rate. Daytona bills $0.0504 per vCPU-hour plus $0.0162 per GiB-hour, identical to E2B's rates. A 2 vCPU, 4 GiB sandbox comes to about $0.17 per hour, which is $120.89 across a 730-hour month. Per-second billing and stopped-state disk-only pricing soften that for bursty work, but a sandbox that stays busy pays list rate.
Fourth, the isolation fine print. Daytona's own docs are ambiguous about what a default sandbox is: the sandboxes page says "Sandboxes run as Linux containers by default" two sentences after promising a dedicated kernel, the isolation docs describe an isolated container with dedicated namespaces and cgroup-enforced resource limits, and no page names the container runtime or the hypervisor. Pause, resume, fork, and hot memory snapshots belong to the separate VM sandbox class, and "VM sandboxes can currently only be created from existing VM snapshots." Default per-sandbox resources also cap at 4 vCPU, 8 GiB RAM, and 10 GiB disk unless you ask for more. If your threat model needs to know exactly what boundary a default sandbox gets, the docs do not say; guaranteed VM isolation means architecting around the VM class deliberately.
Being fair to Daytona matters too, because the roundups attacking it keep citing fixed or false problems. It does sell GPUs: preemptible rates run from $0.57 per hour for an RTX 4090 up to $4.08 for a B300, even though several ranking pages still say it lacks GPU support. Its sandboxes genuinely run indefinitely, with a configurable 15-minute auto-stop default rather than a hard session cap. And its $120.89 baseline month is mid-pack, not an outlier. Check your actual reason for leaving before you migrate.
The 8 best Daytona alternatives in 2026
Agent37 is what we build, so weigh this entry accordingly. It is a persistent sandbox API: POST /v1/instances provisions an isolated sandbox that stays up until you delete it, with files, memory, and installed tools intact between calls. The rate is $0.80 per vCPU plus $0.70 per GB RAM plus $0.09 per GB disk per 730-hour month, so the 2 vCPU, 4 GB baseline is $4.76 always-on, and a sleeping sandbox pays disk alone (about $0.36 per month). Unlike Daytona, the isolation stack is documented by name: standard sandboxes run under gVisor with deny-by-default egress, and vm instances ("a whole Linux machine with its own kernel" per the docs, for Docker, Kubernetes, or anything else that needs a real kernel) are publicly priced at 2.5x the compute rate, $11.36 for the baseline shape. Nine system templates cover Hermes, OpenClaw, Claude Code, Codex, OpenCode, and Grok among others, and custom templates build from any registry image or a Dockerfile. Honest limits: US servers only (Daytona offers US and EU shared regions), CPU only, instance-count caps that rise with top-up history, and support is email plus a dashboard chat, not an enterprise desk.
E2B is the obvious lateral move, and the pricing will feel familiar: its compute rates match Daytona's to the digit, so the baseline month is the same $120.89. What changes is the packaging. E2B names its stack (every sandbox is a Firecracker microVM), its core is Apache-2.0, and E2B Embed (September 30, 2026) packages the core runtime and dashboard for single-host self-hosting (secrets, volumes, and workload identity stay cloud-only), which makes E2B more open than Daytona today, a reversal worth noticing. The trade is session caps: 1 hour on the free Hobby plan, 24 hours with the $150-per-month Pro subscription, multi-day only on Enterprise. Daytona has no session cap at all. We compared E2B's own alternatives separately.
Northflank publishes the lowest raw rates of the general-purpose platforms here: $0.01667 per vCPU-hour plus $0.00833 per GB-hour, $48.66 for the baseline month. It also answers the two questions Daytona leaves open: isolation is selectable and named (Kata Containers microVMs or gVisor), and it deploys into your own AWS, GCP, or Azure account. Its on-demand H100s are published at $2.74 per hour, under Daytona's own on-demand H100 rate of $3.95. The trade: it is a general deployment platform wearing a sandbox hat, with no memory-snapshot primitives.
Morph is the answer if what you wanted from Daytona was fork and hot snapshots without the VM-class ceremony. Infinibranch captures memory, disk, and running processes and branches a warm environment in under 250 milliseconds, as the core product rather than a gated class. Billing is compute units at $0.05 per unit-hour; the baseline shape meters two units an hour, $73.00 for the month. The hypervisor and security model are thinly documented, and the unit math takes a whiteboard.
Cloudflare Sandboxes bill active CPU only: $0.072 per vCPU-hour while the CPU is busy, plus $0.009 per GiB-hour of provisioned memory and a small provisioned runtime-disk charge, on the $5 Workers Paid plan. An agent that mostly waits on an LLM barely pays for CPU. At full use the baseline month is $145.28 (its sizing rules require at least 3 GiB per vCPU, so the math uses 6 GiB, plus 4 GB of disk at Cloudflare's published disk rate). Isolation is a Firecracker microVM per instance. Caps are real: 4 vCPU and 12 GiB per sandbox, a TypeScript-only SDK inside Workers, and instances can be evicted.
Vercel Sandbox runs Firecracker microVMs billed on active CPU: $0.128 per active-CPU-hour plus $0.0212 per GB-hour provisioned, $248.78 at full tilt, the priciest row here. In exchange you get a genuinely free Hobby tier (5 active-CPU hours a month, 45-minute sessions), persistent sandboxes that auto-save and resume, a fork primitive, and a newer Python SDK alongside TypeScript. Snapshots are filesystem-only. It fits teams already on Vercel whose sandboxes idle a lot.
Fly.io Sprites sell each agent a persistent little computer that sleeps when idle and wakes with files intact, billed on actual usage: $0.0385 per CPU-hour and $0.021875 per GB-hour actually used, $120.09 full-tilt and pennies when mostly idle. Checkpoints cover the filesystem, not memory. There are no session caps, and no tier ladder standing between a new account and the open internet.
Modal Sandboxes make sense when sandboxes sit next to the rest of your compute, and Modal is the strongest GPU story in this list. Rates are $0.00003942 per physical-core-second plus $0.00000667 per GiB-second (a Modal core is two vCPUs), $173.71 for the baseline month, with a recurring $30 monthly credit. Modal now offers a full-VM runtime alongside gVisor, mirroring Daytona's two-class split. Sandboxes hard-stop at 24 hours, and memory snapshots are still experimental.
Worth a look beyond the eight: Blaxel meters only active RAM-seconds ($120.89 for the baseline at full use) and resumes from standby in about 25 milliseconds, with up to $200 in credits; Hopx copies E2B's rates and also advertises $200; Runloop builds eval-grade devboxes but gates suspend and resume behind a $250-per-month plan; Tenki is new and matches E2B's rates to the digit; Prime Intellect is running launch pricing through December 22, 2026 ($65.70 for the baseline month), with the usual caveat that promotional rates change; and Together Code Sandbox, the former CodeSandbox SDK, now labels its documented SDK legacy, so verify before committing.
Daytona alternative pricing: one workload, checked October 12, 2026
The honest way to compare sandbox platforms is to price one identical workload everywhere. The table uses the same baseline as our sandbox pricing guide: 2 vCPU, 4 GB RAM, 730 aggregate running hours, published rates only, before credits and plan fees. Active-CPU platforms (Cloudflare, Vercel, Sprites) assume full CPU use here and cost less when agents idle.
Platform | Rate basis | 2 vCPU + 4 GB, 730h | Session cap | Free credit or tier |
Agent37 | Provisioned, while awake | $4.76 | None | $5 credit with card on file |
Northflank | Provisioned | $48.66 | None | Free tier (2 services) |
Morph | Compute units | $73.00 | Snapshot-native | $0 tier, buy units |
Fly.io Sprites | Actual CPU + RAM used | $120.09 | None, sleeps idle | $30 one-time |
Daytona | Provisioned | $120.89 | None, 15-min auto-stop default | $200, not valid for GPUs |
E2B | Provisioned | $120.89 | 1h Hobby, 24h Pro ($150/mo) | $100 one-time |
Cloudflare Sandboxes | Active CPU + provisioned RAM + runtime disk | $145.28 | Evictable, no fixed cap | $5/mo plan allowances |
Modal Sandboxes | Max(requested, used) | $173.71 | 24h hard max | $30/mo recurring |
Vercel Sandbox | Active CPU + provisioned RAM | $248.78 | 45m Hobby, 24h Pro | Hobby monthly allowance |
Three footnotes that change decisions. Daytona's first 5 GiB of disk is free (the pricing page does not say whether that is per sandbox or per account), so a single stopped Daytona sandbox at the 3 GiB default disk costs nothing, where this table's Agent37 figure includes 4 GB of retained disk. E2B, Daytona, Hopx, and Tenki publishing identical compute rates is not an arbitrage opportunity; credits, caps, network tiers, and plan fees are where they actually differ. And Daytona's $200 credit excludes GPU sandboxes, so price GPU work at list rates from day one.
Agent37 vs Daytona: the direct comparison
The two platforms agree on the thesis: agents need sandboxes that persist, not disposable interpreters. Both expose a provision-once API, both let sandboxes live indefinitely, and both bill stopped sandboxes for storage rather than compute. The differences are cost per sustained hour, isolation documentation, and lock-in surface.
On cost, the gap is structural. At the baseline shape, Daytona meters about $0.17 per running hour, Agent37 about $0.006 per awake hour plus retained disk. Keep the shape awake all month and it is $120.89 against $4.76. Run it an hour a day and it is roughly $5 a month at Daytona's rates against about $0.54 on Agent37. Daytona claws some back on genuinely bursty work, since its first 5 GiB of disk is free (scope unstated on the pricing page) while an idle Agent37 sandbox keeps paying its $0.36 disk line, but that only matters below a few running hours per month.
On isolation, Agent37 documents its stack by name: gVisor kernel-level isolation for standard sandboxes, deny-by-default egress, SOC 2 Type I audited with Type II in progress, and publicly priced vm instances with their own kernel at 2.5x compute when you need Docker, Kubernetes, or KVM inside. Daytona advertises HIPAA, SOC 2, and GDPR compliance, but its docs describe the default class in conflicting terms (a dedicated kernel on one line, Linux containers with namespaces and cgroups on another), name neither a container runtime nor a hypervisor, and gate VM capabilities behind a class you can only create from existing VM snapshots. For the underlying tradeoff, see our microVM vs container guide.
On tiers, both companies gate scale by top-up history, so compare the gates that bite you. Agent37 caps how many instances you can run (1 before a top-up, then 10, 50, and 200 as totals rise). Daytona caps the resource pool and restricts network egress until Tier 3's $500 top-up. For a single always-on agent, neither gate matters; for a fleet behind a product, price the tier you actually need.
Where Daytona wins: GPUs, Windows and macOS sandbox classes, an EU shared region, sub-90ms cold starts, warm pools, and five SDK languages. If your workload is GPU inference or computer use on desktop OSes, Daytona is the better fit, and none of the eight alternatives above replaces all of that. Where Agent37 wins: sustained-hours price, named isolation, agent-ready templates, and a pricing page that publishes a comparison of more than 30 providers at published rates with a refund-the-difference guarantee. Plenty of teams run both: Daytona for burst code execution or GPU jobs, Agent37 under the long-lived agents doing recurring work.
If you ran the open-source Daytona dev environment manager
A meaningful share of people searching for a Daytona alternative are not sandbox customers at all. They ran the original product: the Apache-2.0 development environment manager that daytonaio/daytona hosted until April 2025, when the pivot replaced the repo's contents with the AI sandbox platform. That tool's last release was v0.53.0 in February 2025, and it is unmaintained.
For that use case, the living alternatives are DevPod (MPL-2.0, from the vCluster Labs team, closest to Daytona's original client-only architecture), Coder (AGPL core with a commercial tier, self-hosted control plane), Ona (the platform formerly named Gitpod; Gitpod Classic sunset in October 2025 and self-hosting is now enterprise-only), and Devbox (Apache-2.0, Nix-based local environments). For the sandbox platform's code itself, the final AGPL release v0.190.0 remains forkable in the archived repo, and a community continuation called Nightona exists but shows little activity since September 2026. Treat a fork as a commitment: the company states the repo "will receive no further updates, fixes, or releases."
How to choose
Code interpreter inside your product, seconds to minutes per run: stay on Daytona or E2B, or take Cloudflare Sandboxes if you are on Workers and your agents idle.
Always-on or scheduled agents that must remember yesterday: Agent37, with Fly.io Sprites as the usage-billed alternative.
Fork-heavy agent search from warm states: Morph, or Daytona's VM class if you are staying.
Auditable isolation or run-in-your-own-cloud: Northflank, or self-host E2B Embed on one box.
GPUs: Modal or Northflank among the alternatives, and note that Daytona itself sells GPUs, so GPU need alone is not a reason to leave.
Open source as a requirement: E2B's Apache-2.0 core plus Embed, or fork Daytona v0.190.0 under AGPL and own the patches.
FAQ
What is the cheapest Daytona alternative?
For sustained workloads, Agent37: $4.76 for a 2 vCPU, 4 GB sandbox over a 730-hour month against $120.89 at Daytona's published rates. For raw rates on a general platform, Northflank at $48.66. For bursty, mostly-idle agents, Cloudflare and Vercel bill active CPU only, so the winner depends on your idle ratio. Prime Intellect's $65.70 launch pricing also undercuts Daytona's list rate, but it expires December 22, 2026.
Is Daytona still open source?
No. Daytona announced it was going closed source on June 11, 2026, citing AI-assisted vulnerability hunting, shipped the final AGPL-3.0 release (v0.190.0) on June 23, and archived the GitHub repository on October 3, 2026. The old code remains public and forkable at that tag, but the company states it will receive no updates or fixes. Pages still describing Daytona as open source or AGPL-licensed are describing the pre-June product.
Can you self-host Daytona?
Not the current platform. The official self-hosting docs were removed in June 2026, and today's closest option is BYOC ("bring your own compute"), where your servers join a custom region but Daytona's cloud control plane still manages them. Self-hosting the archived v0.190.0 release under AGPL is possible but unmaintained. If self-hosting is the requirement, E2B Embed (single host, Apache-2.0) or Northflank's bring-your-own-cloud are the maintained paths.
Does Daytona run VMs or containers?
Both, as separate classes. The docs say sandboxes "run as Linux containers by default," isolated with namespaces and cgroup limits, while also promising a dedicated kernel, and Daytona does not publicly name the runtime behind either phrase. Pause, resume, fork, and hot memory snapshots require the VM class, which can only be created from existing VM snapshots. Windows, macOS, and GPU workloads are also distinct classes. If you assumed every Daytona sandbox was a microVM, check which class you are actually running.
Which Daytona alternatives offer GPUs?
First, Daytona itself does: preemptible GPUs from $0.57 per hour (RTX 4090) to $4.08 (B300), on-demand from $0.99 to $6.25, and the $200 free credit does not apply to either. Among alternatives, Modal has the deepest GPU integration and Northflank publishes H100s at $2.74 per hour. E2B, Agent37, Cloudflare Sandboxes, and Vercel Sandbox are CPU-only.
Ready to price your own workload? The Agent37 Cloud API runs persistent sandboxes from $4.76 per month with a $5 starter credit once a card is on file, and the pricing page publishes a live comparison of more than 30 providers with a refund-the-difference guarantee, so you can check our math before you spend a dollar.
Written by
Founder at Agent37, which runs managed hosting for OpenClaw and Hermes agents for 1,000+ users. Writes about what actually breaks when you leave an AI agent running.