Top AI Sandboxes For Running Coding Agents In 2027

Coding agents do their best work when they can run what they write: install packages, execute tests, start a server and check the result. Doing that on a developer’s laptop or a shared build box is risky, because agent-generated code can reach SSH keys, cloud credentials and the rest of the network in milliseconds. That is why a new category has grown up around agent sandboxes: isolated, disposable or resumable machines built for AI to run code in.

This list ranks the ten AI agent sandboxes worth comparing in 2027, for teams running coding agents, code interpreters and background agents at scale. We compared isolation, persistence, session limits, GPU access, private-cloud options and published list prices, using vendor documentation and public comparisons from September to November 2026. Prices change often, so treat the rates below as a starting point and confirm them before you commit.

AI Agent Sandboxes At A Glance

Sandbox	Isolation	Best For	Known For
E2B	Firecracker microVMs	Agent products built from scratch	Pause, resume and fork with memory intact
Daytona	Containers, with VM and Windows options	Full dev environments for agents	Fast startup and multi-OS support
Modal	gVisor, with a VM runtime	GPU work inside the sandbox	Sandboxes on a serverless GPU platform
Vercel Sandbox	Firecracker microVMs	Teams already on Vercel	Billing only for active CPU time
Cloudflare Sandbox	Container inside its own VM	Teams on Cloudflare Workers	Low cost and preview URLs
Northflank	Kata Containers or gVisor	Running sandboxes in your own cloud	Self-serve BYOC and Kubernetes
Runloop	VMs on a custom hypervisor	Running and evaluating coding agents	Managed agent processes and evals
Blaxel	microVMs	Agents that sleep and wake often	Fast resume from standby
Freestyle	KVM virtual machines	Locked-down agent workloads	Deny-by-default network egress
Fly.io Sprites	Firecracker microVMs	Persistent personal agent machines	Agent CLIs preinstalled and free idle time

Best AI Sandboxes For Coding Agents In 2027

1. E2B — The Agent-Native Sandbox With Pause, Resume And Fork

E2B was built for AI agents from the start. Each sandbox is a Firecracker microVM, and a running sandbox can be paused with its memory and files, resumed in about a second, or forked into as many as 20 copies in one call, which suits agents that branch to try several approaches. SDKs cover Python, JavaScript and TypeScript, with ready integrations for the OpenAI Agents SDK, Vercel AI SDK, LangChain and others, plus cloud browsers, desktop sandboxes and an MCP gateway.

Sessions run up to one hour on the free Hobby tier and 24 hours on Pro. List rates in autumn 2026 comparisons were about $0.05 per vCPU-hour, paused sandboxes cost nothing, and enterprise customers can deploy into their own AWS, GCP or Azure account. The runtime is also available to self-host under the Apache-2.0 license. There is no GPU inside the sandbox.

2. Daytona — Full Development Environments With Fast Startup

Daytona gives agents full development environments rather than bare code runners. Sandboxes run as containers by default, with VM and Windows options, and include Git, language servers, a terminal, SSH, a computer-use desktop and an MCP server. Daytona has competed hard on startup speed, and its pause and fork features became stable during 2026.

GPU instances are available, and bring-your-own-cloud deployment is offered on enterprise plans. Published CPU and memory rates in late 2026 comparisons matched E2B’s. It suits teams that want agents working in something close to a developer’s real workspace.

3. Modal — Sandboxes On A Serverless GPU Platform

Modal is the pick when agent code needs a GPU. Its sandboxes sit inside Modal’s serverless platform, isolated with gVisor, and a VM-based sandbox runtime became generally available on October 1, 2026. Sessions run up to 24 hours, filesystem snapshots let you restore work into a new sandbox, and examples show Claude Code and OpenCode running inside.

The main thing to budget for is price. Sandbox compute is billed at a higher rate than Modal’s general serverless functions, so CPU-only workloads usually cost more here than on E2B or Cloudflare. For teams already running inference or batch jobs on Modal, keeping sandboxes on the same platform is often worth it.

4. Vercel Sandbox — Active CPU Billing For Agents That Mostly Wait

Vercel Sandbox runs agent code in Firecracker microVMs attached to the Vercel platform. Sandboxes are persistent by default, snapshot automatically when stopped, and run up to 45 minutes per session on Hobby and 24 hours on Pro. An egress firewall supports deny-all and allowlists, and credentials can be brokered at the firewall so secrets never sit inside the sandbox.

Its pricing model is the distinctive part. Vercel bills active CPU time, so an agent that spends most of its life waiting on a model is not charged for idle compute, although its per-hour CPU rate is the highest on this list. It is the natural choice for teams already deploying on Vercel, and its SDK and CLI are open source.

5. Cloudflare Sandbox — Low-Cost Sandboxes For Teams On Workers

Cloudflare’s Sandbox SDK reached version 1.0 on September 30, 2026. Each sandbox is a container running in its own VM, with a persistent code interpreter, a terminal and preview URLs that expose a running app for review. Sandboxes sleep after ten minutes idle, and directories can be backed up to R2 storage.

Rates in autumn 2026 comparisons were among the lowest on this list, although the service requires Cloudflare’s paid Workers plan. It fits best when the rest of your agent stack already runs on Workers.

6. Northflank — Sandboxes In Your Own Cloud, Without An Enterprise Contract

Northflank runs sandboxes on Kata Containers with Cloud Hypervisor, or on gVisor, with no fixed session limit and GPU support. Its standout feature is self-serve bring-your-own-cloud: teams can run sandboxes in their own account on the major clouds or on their own Kubernetes cluster, which matters when code and data cannot leave a controlled environment.

Northflank is a general application platform as well, so sandboxes sit next to databases, queues and cron jobs. Its published CPU rate was among the lowest in late 2026 comparisons, and sandboxes that scale to zero cost only their storage.

7. Runloop — Sandboxes Built To Run And Evaluate Coding Agents

Runloop goes further than a bare sandbox by running and managing the agent process itself. Its VMs run on a custom hypervisor with disk snapshots and fan-out, plus a Playwright browser, an MCP hub and built-in tools for evaluating agents against benchmarks and your own test sets.

That evaluation focus makes it a strong fit for companies building coding agents, not just using them. Suspend and resume require the Pro plan, and enterprise customers can deploy into their own VPC.

8. Blaxel — Fast Resume For Agents That Sleep And Wake Often

Blaxel runs sandboxes as microVMs with memory, disk and process snapshots, so a sandbox can drop into standby and resume quickly with its state intact. It can also fork a sandbox, gives each one its own MCP server, and offers templates for browsers and Jupyter.

Billing is based on memory while a sandbox is active, which suits agents that run in short bursts throughout the day. Blaxel also supports bring-your-own hardware and private VPC interconnects for teams with data residency needs. There is no GPU inside the sandbox.

9. Freestyle — Locked-Down VMs With Deny-By-Default Egress

Freestyle runs sandboxes as full KVM virtual machines with memory and disk snapshots, and it can fork a running VM. Network egress is denied by default, so code cannot call out to the internet unless you allow it, and SSH, terminal access and private networks are available.

Its list rates were competitive in autumn 2026 comparisons. It suits teams that want the security posture of a full VM with strict network rules for untrusted, agent-written code.

10. Fly.io Sprites — Persistent Agent Machines With The CLIs Already Installed

Sprites, from Fly.io, are persistent Firecracker microVMs with filesystem checkpoints of up to 100 GB. They come with the Claude Code, Codex, Gemini and Cursor command line tools preinstalled, and each Sprite can expose a hosted remote MCP server.

The pricing is friendly to long-lived personal agent machines: compute costs nothing while a Sprite is idle. It is less suited to fleets of short, disposable runs, but very convenient for developers who want a cloud machine their agent can keep working in.

How To Choose An AI Agent Sandbox

How Strong Does Isolation Need To Be?

If you run code from untrusted users or let agents act on sensitive repositories, prefer a separate kernel per sandbox, such as Firecracker or KVM microVMs, over plain containers. Pair isolation with the controls in our guide on how to secure AI agents and MCP integrations.

Does State Need To Survive Between Runs?

Short code-interpreter calls can be thrown away. Coding agents that work on a repository for hours need persistence, snapshots and ideally pause and resume with memory, which E2B, Blaxel and Freestyle handle well.

Do You Need GPUs Or Your Own Cloud?

Only some platforms put a GPU in the sandbox, with Modal, Daytona and Northflank among them. If code or data must stay in your own account, look at Northflank’s self-serve BYOC or the enterprise BYOC options from E2B, Daytona, Runloop and Blaxel.

How Will You Pay For Idle Time?

Agents spend much of their time waiting on a model. Vercel bills only active CPU, E2B charges nothing for paused sandboxes and Sprites cost nothing idle, while others bill the whole time a sandbox is running. Model your real usage before comparing per-hour rates.

How Will You Watch What Agents Do?

A sandbox limits damage, but it does not tell you what happened. Add tracing and cost tracking from our list of observability tools for AI coding agents, and check how each sandbox fits the AI agent frameworks you already use.

Conclusion

E2B leads this list as the most complete agent-native sandbox, with Firecracker isolation and pause, resume and fork that coding agents actually use. Daytona is the strongest choice for full development environments, Modal for anything that needs a GPU, and Vercel and Cloudflare for teams already on those platforms. Northflank stands out for running sandboxes in your own cloud, Runloop for building and evaluating agents, and Blaxel, Freestyle and Fly.io Sprites each solve a specific problem well. Match isolation to your risk, persistence to your agent’s workload and pricing to how much time your agents spend waiting.