E2B Alternatives: 9 Sandboxes for AI Agent Code

The best E2B alternative depends on what your agent needs that E2B isn't giving you. If you need GPUs next to your sandbox, look at Modal or Daytona. If you already deploy on Vercel or Cloudflare, use their built-in sandboxes. If you need sandboxes inside your own cloud account, look at Northflank or Runloop. If idle time is your biggest cost, look at Blaxel or Fly Sprites. If you want everything on your own hardware, run Microsandbox, or run E2B itself.

That last option surprises people. E2B's backend is open source under Apache-2.0, and it now ships a single-machine package for self-hosting. So "leave E2B" and "leave E2B Cloud" are two different decisions.

One more thing changed this year. Daytona, the alternative most roundups list first, moved its core code to a private codebase in June 2026. If you picked it because it was open source, read that section before you migrate.

Quick Comparison

Why Teams Look Past E2B

Start with what E2B does well, because it sets the bar.

The E2B runtime gives every sandbox its own Firecracker microVM, with a per-sandbox egress firewall and domain allow and deny lists. A new sandbox is restored from a snapshot instead of booted from scratch. Sandboxes can pause, resume and fork, with up to a hundred forks per request. Persistent volumes outlive the sandbox.

On E2B's pricing page, usage is billed per second of a running sandbox, on top of a plan. The plan sets session length and concurrency: up to 1 hour on the Hobby plan, up to 24 hours on Pro, and multi-day sessions plus BYOC on Enterprise.

So the reasons to switch are usually about fit:

• Your agent needs a GPU. E2B sandboxes are CPU machines. Agents that train, fine-tune or run local models need a provider that attaches GPUs.
• Sessions run longer than your plan allows. Coding agents that work for a day, or keep a dev server alive between instructions, run into session caps.
• You pay for idle time. Agents spend a lot of time waiting on the model. Some providers stop charging for CPU while the sandbox waits.
• Data has to stay in your account. Regulated teams often need the sandbox inside their own VPC without an enterprise contract.
• You're already on a platform. A sandbox from your existing host means one bill.

The Best E2B Alternatives

Daytona: GPUs, Windows and long-lived sandboxes, now closed source

Best for: agents that need GPUs, Windows or macOS sandboxes, or state that lasts for weeks.

Daytona sandboxes come in several classes. Daytona's isolation docs describe the default as an isolated container with its own namespaces and resource limits, and VM sandboxes (Linux VM and Windows) as full virtual machines with their own kernel. The docs also list GPU sandboxes on cards from RTX 4090 up to B300, in on-demand and spot modes, plus snapshots, volumes, forking, and auto-stop, auto-archive and auto-delete controls.

Daytona's pricing page bills compute, memory and storage per second, pay as you go, with enterprise options for SSO, audit logs and BYOC.

The trade-off: Daytona is no longer open source. The company's June 11, 2026 post says it moved its production codebase to closed source for security reasons. The old GitHub repo is archived. It stays public under AGPL-3.0, but gets no updates, fixes or releases. If self-hosting was your reason for picking Daytona, that reason is gone. And the default sandbox is a container, so pick the VM class if you want a kernel boundary.

Modal Sandboxes: when the agent also needs GPUs

Best for: teams already running inference or training on Modal, or agents that need a GPU inside the sandbox.

Modal's sandbox guide describes two runtimes. gVisor, Google's user-space kernel, is the default for most workloads. A VM runtime gives the sandbox its own Linux kernel, for jobs like running Docker inside the sandbox. Sandboxes default to a 5-minute lifetime and accept a timeout of up to 24 hours. For longer work, Modal recommends filesystem snapshots and restoring them into a new sandbox.

Billing is per second for CPU, memory and GPU. Modal's pricing page notes sandboxes are billed at non-preemptible rates.

The trade-off: gVisor intercepts system calls instead of running a separate kernel, so some low-level tools behave differently. Modal is a managed platform only. There's no self-host or BYOC option.

Vercel Sandbox: when your app already runs on Vercel

Best for: Next.js apps and AI SDK projects that want a sandbox without another vendor.

Vercel Sandbox runs each sandbox in a Firecracker microVM with its own filesystem and network, the same isolation tech as E2B. Persistence is the default: sandboxes auto-save state on stop and resume where they left off. It also supports custom OCI images, a firewall, mountable drives, and per-agent Linux users for multi-agent setups.

The pricing page bills Active CPU (time the CPU actually works, not time spent waiting on network or model calls), provisioned memory, sandbox creations and data transfer. Maximum session length is 45 minutes on Hobby and 24 hours on Pro and Enterprise.

The trade-off: it's tied to the Vercel platform, with no BYOC or self-host route. The SDK is open source, but the runtime isn't.

Cloudflare Sandboxes: when your app runs on Workers

Best for: teams building agents on Cloudflare Workers and Durable Objects.

Cloudflare Sandboxes let a Worker start a Linux instance and send it work. Cloudflare's docs say each instance is a microVM with its own kernel and network, and that internet traffic reaches it only through your Worker. You control which APIs and data the code receives, and whether it can reach the internet. There are guides for running Claude Code, Codex and other coding agents inside a sandbox, and for saving workspaces to R2.

Sandboxes run on Cloudflare Containers, which bill for every 10ms an instance is actively running, and need the Workers Paid plan.

The trade-off: the lifetime model takes some learning. The docs warn that an idle instance is still billed until it stops, and that files survive a restart only if the instance kept running or your app saved a snapshot.

Northflank: when you need it in your own cloud account

Best for: companies running each customer's agent in its own sandbox, especially inside their own VPC.

Northflank's sandbox product runs microVMs on Cloud Hypervisor, each with its own guest kernel, and switches to gVisor for GPU sandboxes. You can run them on Northflank's cloud or on BYOC clusters in AWS, Google Cloud, Azure, Oracle or bare metal, and the control plane can be deployed into your own infrastructure. Sandboxes can be short-lived per task or long-running with volumes, and compute is billed by the second.

The trade-off: Northflank is a full deployment platform, not a sandbox SDK. You get more control, but a broader API than E2B's create-and-run flow.

Blaxel: when your agent spends most of its time waiting

Best for: agents with long idle gaps between steps.

Blaxel runs one microVM per agent, app or job. Sandboxes scale to zero when idle and resume their full memory state in about 25 milliseconds, by Blaxel's figure, and suspended time doesn't count toward active CPU. Beyond sandboxes, it offers batch jobs, volumes, an egress proxy that injects secrets, and a model gateway.

Pricing is usage-based, pay as you go. For data residency, Blaxel's "bring-your-own-metal" option runs the sandbox runtime on bare-metal servers in your own VPC, connected to Blaxel's control plane.

The trade-off: Blaxel isn't open source. Its agent runtime for long-running sessions was still marked "coming soon" at the time of writing.

Runloop: when you're building or evaluating coding agents

Best for: teams shipping coding agents who also need benchmarks and evals.

Runloop calls its sandboxes Devboxes. They're microVM environments with snapshot and branch support for disk state, SSH and IDE access, repo connections that infer a build environment, and both arm64 and x86 support. Around them sit tools for evaluating agents and a credential gateway so agents never see raw secrets. Enterprise customers can deploy Runloop into their own cloud account.

Pricing is a plan plus usage, billed per CPU-hour, GB-hour and storage.

The trade-off: Runloop is built around software-engineering agents. If you just need a quick code interpreter for a chatbot, it's more platform than you need.

Fly Sprites: when each agent should keep its own Linux box

Best for: coding agents that install once and come back to the same machine.

Fly Sprites are Fly.io's agent sandboxes: hardware-isolated Linux computers with a disk that survives sleep, filesystem checkpoints in about a second, and an HTTPS URL that wakes the Sprite on request. They scale to zero when idle. Billing is based on actual CPU, memory and storage usage, with cheaper rates for cold storage.

If you'd rather build your own orchestration, Fly Machines are the lower-level option: fast-booting VMs you start and stop through an API.

The trade-off: Sprites are a newer product built for persistence, not for spinning up thousands of throwaway sandboxes per minute. Creation rate limits depend on your plan tier.

Microsandbox: when everything has to run on your hardware

Best for: local-first agents, CI jobs and self-hosted platforms.

Microsandbox is an Apache-2.0 microVM runtime and library. It runs standard OCI images, forks and snapshots live sandboxes, works on Linux, macOS and Windows, and has SDKs for Python, TypeScript, Rust and Go. The msb CLI feels like Docker: images, volumes, shells and named sandboxes.

The trade-off: the README calls it beta software and warns of breaking changes. There's no managed service, so scaling, scheduling and patching are on you. The repo also moved organizations this year, so update any old links.

E2B self-hosted: when you like E2B but not E2B Cloud

Best for: teams happy with E2B's SDK who need data to stay put.

The open-source backend that runs E2B Cloud is the same code you can deploy yourself. E2B Embed runs the whole stack on a single machine, with Docker Compose, Terraform for GCP, AWS and Azure, or Kubernetes. It uses the same SDK and API as E2B Cloud, so your agent code doesn't change.

The trade-off: you now run Firecracker hosts yourself, which means Linux servers with virtualization support and someone on call.

How to Choose an E2B Alternative

Then check isolation, because "sandbox" covers very different boundaries:

• MicroVMs (Firecracker, Cloud Hypervisor) give each sandbox its own kernel. This is the strongest common boundary for untrusted, AI-generated code. E2B, Vercel, Northflank, Blaxel, Runloop and Microsandbox use it.
• gVisor puts a user-space kernel between the code and the host. It's strong and flexible, especially for GPUs, but a few syscalls behave differently. Modal and Northflank's GPU sandboxes use it.
• Containers share the host kernel. They're fast and cheap, but a kernel bug can break the boundary. Daytona's default class is a container, with VM sandboxes as an option.

Before you migrate, test cold start with your real image, a full agent session, and a pause and resume with real files on disk.

If you're still choosing the agent framework that will call the sandbox, our guides to LangChain alternatives and OpenAI Agents SDK vs Claude Agent SDK cover that layer. For open-source coding agents that need a sandbox underneath, see OpenHands alternatives.

Where E2B Is Still the Right Call

Stay on E2B if:

• You want microVM isolation with the simplest SDK. Create a sandbox, run code, read the result. Few alternatives are this direct.
• You may need to self-host later. The runtime is Apache-2.0, and Embed runs it on your hardware with the same API. Daytona no longer offers that path.
• Your agents fork often. Forking a live sandbox, up to a hundred at a time, suits tree search and parallel attempts.
• You need fine-grained egress control. Per-sandbox domain allow and deny lists are built in.

Where Taku Fits

Taku isn't a code sandbox, and it doesn't replace E2B or anything on this list. It helps with a different problem: someone has already built a working AI app on top of one of these sandboxes, and you'd rather use it than wire up the infrastructure yourself.

That's where Taku comes in. Taku Apps and Sites, built by the best AI minds. Find one, run it, and keep it in your Mac Dock. Taku is in Beta, and the Mac app is available now. You can browse what's there in the marketplace.

FAQ

Who are E2B's main competitors?

Daytona, Modal, Vercel Sandbox, Cloudflare Sandboxes, Northflank, Blaxel, Runloop and Fly Sprites are the most common. Modal and Daytona stand out for GPUs, Vercel and Cloudflare for platform fit, and Northflank and Runloop for running inside your own cloud.

What is the best open source E2B alternative?

Microsandbox, an Apache-2.0 microVM runtime you can run locally or on your own servers. E2B itself is also open source, and E2B Embed lets you self-host the full stack. Daytona was a common answer until June 2026, when it moved to closed source and archived its public repo.

What is the best self-hosted code sandbox for AI agents?

If you want E2B's SDK, self-host E2B with Embed. If you want a lightweight local runtime, use Microsandbox. If you want a managed control plane with compute in your own account, look at Northflank BYOC or Runloop's VPC deployment.

E2B vs Daytona: which is better?

E2B gives every sandbox a Firecracker microVM and keeps its runtime open source. Daytona offers more sandbox types, including GPU, Windows and VM sandboxes, plus long-lived state, but its default sandbox is a container and its code is now closed source. Pick E2B for isolation and openness, Daytona for GPU and OS variety.

E2B vs Modal: which is better?

Pick Modal if your agent needs GPUs or you already run models on Modal. Pick E2B if you want microVM isolation, a sandbox-first SDK, and a self-host option. Modal sandboxes use gVisor or a VM runtime and run up to 24 hours per sandbox.