For agents that must live 24/7 and keep their state, Molted is the best E2B alternative; for ephemeral sandboxes that run untrusted code in seconds, Daytona and Modal are the better picks. Two different jobs hide behind one search: this list ranks both, and tells you which is which.
E2B is a genuinely good product for what it is built for: secure, fast Firecracker microVM sandboxes that an agent spins up, uses to run code, and tears down. But a growing share of teams searching for E2B alternatives are actually asking a different question: how do I keep an agent alive for days or weeks, not seconds? E2B sessions cap out at 24 hours even on paid plans, because it was never designed to be a home for persistent agents. That is not a flaw, it is a scope decision. So this list is segmented honestly: position 1 is a resident runtime, ranked first only for the long-running, always-on need; positions 2 through 7 are the real sandbox alternatives, ranked for ephemeral code execution. Figure out which job you have before you pick.
Molted is our product. It ranks first for one specific need, resident long-running agents, because that is the category it is built for. If you need ephemeral code execution sandboxes, Molted is the wrong tool and the other six entries on this list are better choices.
Best forTeams that want sandboxes plus services, jobs and databases on one platform, especially in their own cloud account.
PricingPer-second billing from roughly $0.017 per vCPU-hour; BYOC bills your cloud account.
02The ranking
01
Molted
Resident agent runtime
The managed operating environment where autonomous agents live, not just execute.
Best for: Agents that must stay alive 24/7, hold state across sessions and act on their own. Not for ephemeral code execution.
Molted is not a sandbox, and it does not pretend to be one. It is a managed operating environment for resident autonomous agents: the agent runs continuously in its own instance, keeps its files and sessions warm, and acts without being invoked. It runs OpenClaw in production today and is runtime-agnostic, with Hermes and Claude Code supported on request. The operational layer is the product: 4-tier self-healing catches crashes in under 60 seconds and has the instance back in under 90, every file lives on a versioned filesystem with point-in-time restore, and a RAM semaphore keeps high density safe so idle agents stay cheap. Agents reach 1,500+ integrations through a managed integration layer, and each agent gets its own mailbox and phone number for email, SMS and voice.
The honest scope: if your workload is 'run this AI-generated Python safely and give me stdout', Molted is the wrong shape. There is no millisecond-scale microVM to spin up on demand, and per-instance per-day pricing makes no sense for sub-second jobs. Molted wins when the sandbox model breaks down: when you find yourself building schedulers, state stores, recovery logic and session management around ephemeral sandboxes to fake a persistent agent. Many teams use both layers: a resident agent on Molted that calls a sandbox like E2B or Daytona when it needs to execute untrusted code.
Pros
Purpose-built for resident agents: persistent state, no per-task spin-up, no 24-hour session ceiling
4-tier self-healing with crashes caught in under 60s and recovery in under 90s
Versioned filesystem with diff and point-in-time restore
1,500+ integrations, plus dedicated email and voice per agent
Cons
Not an ephemeral code execution sandbox: no on-demand microVMs in milliseconds
Per-instance per-day pricing is a poor fit for sub-second or bursty jobs
If you only need to run untrusted code snippets, every other entry fits better
Open-source sandbox infrastructure with sub-90ms cold starts.
Best for: Teams that want fast code execution sandboxes with an open-source, self-hostable escape hatch.
Daytona is the strongest direct E2B alternative for the classic sandbox job. It pivoted to AI agent infrastructure in early 2025 and now focuses on one thing: spinning up isolated environments for AI-generated code as fast as possible, with cold starts under 90ms. The SDK covers the expected surface (execute code, filesystem access, process management) and the platform is backed by a $24M Series A, so it is not a side project.
Its biggest differentiator against E2B is licensing: Daytona is open source under AGPL-3.0 and self-hostable for free, which matters if you have compliance requirements or want to avoid vendor lock-in on a layer this deep in your stack. What it does not do is host resident agents: like every sandbox on this list, the model is spin up, execute, tear down.
Pros
Sub-90ms cold starts, faster than E2B's typical 150 to 200ms
Open source (AGPL-3.0) and self-hostable at no license cost
Per-second usage-based billing with free starting credits
Well-funded and focused entirely on the agent sandbox use case
Cons
Container-based isolation rather than Firecracker microVMs on the default path
Ephemeral by design: persistent, always-on agents are out of scope
AGPL licensing needs legal review if you embed the self-hosted version in a product
Sandboxes on top of one of the best serverless Python platforms.
Best for: Teams already on Modal, or sandbox workloads that need GPUs attached.
Modal built its reputation on serverless Python with an exceptional developer experience: functions, containers, GPUs, queues and cron that feel instant. Sandboxes are its primitive for running untrusted, AI-generated code with the same per-second billing and the same infrastructure underneath. If your team already runs inference or data pipelines on Modal, adding sandboxed code execution is one import away, and nobody else on this list makes it as easy to attach an H100 to a sandbox.
The honest caveats: sandbox compute is priced at a premium over Modal's base serverless rate (roughly 3x the standard CPU rate), and CPU, memory and GPU are billed as separate line items, so real costs need modeling rather than napkin math. Modal is also a code execution platform, not an agent host: long-lived stateful processes cut against the grain of the serverless model it is built on.
Pros
Best-in-class developer experience for Python teams
GPUs attachable to sandboxes, billed per second, which few sandbox vendors offer
One platform for inference, batch jobs and sandboxed execution
Cons
Sandbox compute carries a roughly 3x premium over Modal's base CPU rate
CPU, memory and GPU billed as separate line items makes cost prediction harder
Serverless shape: not designed for agents that stay resident for weeks
Isolated Linux environments on Cloudflare's network, GA since 2026.
Best for: Teams already building on Cloudflare Workers who want sandboxed execution close to their agent logic.
Cloudflare Sandboxes reached general availability in 2026 as part of the company's push into agent infrastructure, built on Cloudflare Containers. Each sandbox is an isolated Linux environment with a code interpreter, PTY terminal support, secure credential injection and snapshot-based session recovery. The standout pricing decision is active CPU billing: you pay for CPU cycles actually used rather than provisioned time, which is genuinely attractive for agents that sit idle between bursts of work.
The trade-off is ecosystem coupling. Sandboxes require a Workers Paid plan and the true cost spans multiple billing dimensions (Workers requests, Durable Objects, memory, CPU), so the headline vCPU rate is not the whole bill. If your stack is already Workers-first, this is the natural pick; if it is not, you are adopting a platform, not just a sandbox SDK. And while snapshots make sessions recoverable, this is still a sandbox model, not a resident runtime.
Pros
Active CPU pricing: pay only for cycles used, idle time is nearly free
Snapshot-based session recovery and persistent code interpreter sessions
Runs on Cloudflare's global network, close to Workers-based agent logic
Cons
Requires the Workers Paid plan; real costs span several billing dimensions
Tightly coupled to the Cloudflare ecosystem; awkward as a standalone choice
Container-based isolation, not Firecracker microVMs
Raw microVMs via API, per-second billing, maximum control.
Best for: Infrastructure-strong teams that want to build their own sandbox or agent layer on primitives.
Fly Machines are Firecracker microVMs you create, start, stop and destroy with a single API call, billed per second while running, deployable across Fly's global regions. Stopped machines cost almost nothing. There is no opinionated agent framework on top: you get a fast, hardware-isolated VM and full control over what runs inside it. In early 2026 Fly added Sprites, persistent microVMs with 100GB of NVMe storage and checkpoint/restore in roughly 300ms, aimed squarely at agent workloads that need durable state.
The honest positioning: this is the right layer for teams with real infrastructure engineering capacity who want to own their sandbox or agent orchestration. Everything E2B gives you as an SDK (lifecycle management, code execution APIs, session handling) is yours to build. That is a feature if you have the team for it and a multi-quarter project if you do not.
Pros
True Firecracker microVM isolation with per-second billing and near-zero stopped cost
Sprites add persistent NVMe storage and ~300ms checkpoint/restore
No platform opinion: build exactly the sandbox or agent layer you want
Cons
No agent- or sandbox-specific SDK: orchestration, recovery and session logic are yours
Meaningful engineering investment before you match E2B's developer experience
Operating a fleet of machines well is an ongoing job, not a one-time setup
MicroVM sandboxes that resume in under 25ms with state intact.
Best for: Teams deploying their own agent code who want fast-resuming sandboxes and serverless agent hosting in one place.
Blaxel sits between raw compute and a managed runtime: it is an infrastructure platform built specifically for AI agents, combining microVM sandboxes, serverless agent hosting endpoints and MCP server hosting. Its signature capability is standby: sandboxes suspend indefinitely at essentially zero compute cost (you pay only for snapshot storage) and resume in under 25ms with full filesystem and memory state intact. For agents with intermittent activity, that pricing shape is hard to beat among sandbox vendors.
What Blaxel does not provide is the agent itself. You bring your own runtime and your own logic for keeping an agent coherent over time; Blaxel gives that code fast, well-isolated infrastructure to run on. It is a strong pick for builders who want more agent-awareness than Fly Machines but more control than a fully managed runtime, with the usual caveat that it is a younger platform than most others on this list.
Pros
Sub-25ms resume with full filesystem and memory state preserved
Standby costs nearly nothing: snapshot storage only, no compute while idle
Agent-focused platform: sandboxes, serverless agent endpoints and MCP hosting co-located
Cons
You bring the runtime: agent logic, recovery semantics and coherence are your code
Younger platform with a smaller ecosystem than Modal or Cloudflare
Suspend/resume is not resident: a suspended agent cannot act on its own
Sandboxes with microVM isolation inside a full developer platform, in their cloud or yours.
Best for: Teams that want sandboxes plus services, jobs and databases on one platform, especially in their own cloud account.
Northflank is a general developer platform (containers, services, cron, databases, CI/CD) that added first-class sandbox capabilities with microVM-grade isolation via Kata Containers and gVisor. Two things make it distinctive as an E2B alternative: some of the lowest published compute rates in the category, billed per second, and self-serve BYOC, meaning sandboxes run inside your own AWS, GCP, Azure or bare-metal account while Northflank provides the control plane. For teams with cloud credits or strict data-residency requirements, that combination is rare.
The flip side of breadth is focus. Northflank is a platform you adopt, not a single-purpose sandbox SDK, and everything agent-specific (session semantics, recovery logic, orchestration) remains yours to design on top of its primitives. It is the right pick when sandboxes are one workload among several you want on unified infrastructure.
Pros
Among the lowest published CPU rates in the category, billed per second
Self-serve BYOC into AWS, GCP, Azure and bare metal
MicroVM-grade isolation via Kata Containers and gVisor
Cons
A full platform to learn, heavier than a focused sandbox SDK
No agent-specific runtime layer: lifecycle and recovery logic is your build
BYOC shifts infrastructure operations partly back onto your team
The verdict
Segment first, then choose. If your workload is ephemeral code execution, stay in the sandbox category: Daytona if you value open source and the fastest cold starts, Modal if you want GPUs and a superb Python experience, Cloudflare if you live in the Workers ecosystem, Fly Machines if you want raw microVM control, Blaxel for fast-resume standby economics, Northflank for BYOC and platform breadth. If your workload is agents that must live 24/7, hold state and act on their own, no sandbox on this list is designed for that job, including E2B. That is the one need where Molted ranks first: a resident runtime with self-healing, a versioned filesystem, and 1,500+ integrations, proven on 11,000+ instances in production.
03How we ranked
The criteria behind the order.
Which job are you hiring for?
Ephemeral code execution (run untrusted code, get output, tear down) and resident agents (stay alive, hold state, act unprompted) are different categories with different winners. We segment every entry by which job it actually serves instead of pretending one tool wins both.
Lifecycle and state
Maximum session length, what happens to filesystem and memory state between runs, and whether persistence is native or something you rebuild with snapshots and rehydration on every invocation.
Isolation and cold start
For sandboxes, the core metric: how strong is the isolation (microVM, gVisor, Kata) and how fast does an environment come up. Milliseconds matter when an agent spins up hundreds of sandboxes per day.
Pricing shape
Per-second billing suits bursty code execution. Flat per-instance pricing suits always-on agents. A mismatch between pricing shape and workload shape is the most common way teams overpay.
04FAQ
The best E2B alternatives in 2026, answered.
01
What is the best E2B alternative?
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It depends entirely on the job. For ephemeral code execution, the closest direct alternatives are Daytona (open source, sub-90ms cold starts), Modal Sandboxes (best if you want GPUs or already use Modal) and Cloudflare Sandboxes (best inside the Workers ecosystem). For agents that need to stay alive continuously rather than execute and exit, the best alternative is not another sandbox at all but a resident runtime like Molted, which is built for always-on autonomous agents.
02
Is E2B good for long-running agents?
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No, and it does not claim to be. E2B sandboxes are ephemeral by design, with sessions capped at 24 hours even on paid plans. You can approximate persistence by checkpointing state and rehydrating it into new sandboxes, but you end up building and maintaining the scheduler, state store and recovery layer yourself. For agents that must live continuously, a resident runtime is the right category.
03
What are the best E2B alternatives for long-running agents?
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The honest answer is that E2B alternatives for long-running agents are not sandboxes at all. Sandbox vendors compete on cold start and per-second pricing for ephemeral execution. A long-running agent needs the opposite: persistent state, self-healing recovery, and a lifecycle measured in weeks. Molted is built for exactly this: a managed environment where agents (OpenClaw today, Hermes and Claude Code on request) run resident with 4-tier self-healing, a versioned filesystem, and 1,500+ integrations through a managed integration layer.
04
What is a resident runtime?
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A resident runtime is an environment where an agent lives continuously instead of being spun up per task. The agent keeps its filesystem, sessions and context warm, can act on its own initiative rather than only when invoked, and is supervised so it recovers automatically when something crashes. It is the opposite lifecycle shape from a sandbox, which exists only for the duration of one task.
05
What are the best sandboxes for AI agents that execute untrusted code?
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Among sandboxes for AI agents, Daytona leads on cold start speed and open-source self-hosting, Modal Sandboxes lead on developer experience and GPU access, Cloudflare Sandboxes lead on idle-friendly active CPU pricing within the Workers ecosystem, and Blaxel leads on fast resume with preserved state. Fly Machines and Northflank are the picks if you want lower-level primitives or BYOC. E2B itself remains a solid default in this category.
06
Can I use a sandbox and a resident runtime together?
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Yes, and many teams should. The two layers are complementary: a resident agent orchestrates work continuously, and calls out to an ephemeral sandbox when it needs to execute untrusted code safely. An agent hosted on Molted can use E2B, Daytona or Modal for code execution and then keep working. What you want to avoid is rebuilding the persistent agent layer (state, recovery, scheduling) around sandboxes by hand.