Best Daytona Alternatives for AI Agents in 2026: Sandboxes, MCP and Cloud Computers Compared

Short answer: The best Daytona alternatives for AI agents depend on what you use Daytona for. For isolated code execution from an SDK, look at E2B (closest match, pause and resume), Modal (GPUs and Python), Vercel Sandbox (apps on Vercel), Northflank (your own cloud) or Cloudflare Sandboxes (Workers apps). For persistent Linux machines per agent, look at Fly.io Sprites or Upstash Box. If what you really wanted was a computer that Claude Code, Codex, Cursor and ChatGPT can all use, with a desktop, Chrome and your logins, Simular Box fits that job without any SDK code. Stay on Daytona if you need Windows, macOS or many GPU types behind one API.

Which Daytona? This guide covers Daytona.io, the platform that runs sandboxes for AI agents and AI-generated code. Daytona started as an open-source manager for developer environments before it moved to AI agent infrastructure; if that is the Daytona you are replacing, look at GitHub Codespaces, Coder or DevPod, covered in our list of cloud computers for developers.

We read each vendor's docs and pricing pages on November 13, 2026, and compared what an agent builder asks first: how long a run can last, what survives between runs, GPUs, a desktop for computer use, how agents connect (SDK or MCP), and the published price. We did not run a shared benchmark, so this guide does not rank the options on speed or cost per task.

What Daytona does today

Daytona runs sandboxes for agents, evaluations and training. Its sandboxes run as Linux containers by default, with Linux VM and Windows VM classes that add fork, pause and resume and memory snapshots, GPU sandboxes from NVIDIA and AMD, and macOS sandboxes on dedicated Apple silicon. It ships SDKs for Python, TypeScript, Ruby, Go and Java, and a computer-use API. Daytona raised a $24M Series A led by FirstMark Capital in February 2026.

Why teams look for a Daytona alternative

• The open-source repository is archived. The daytonaio/daytona repo on GitHub is marked archived (checked November 13, 2026). Teams that chose Daytona to self-host need another plan.
• Memory features depend on the class. Fork, pause and resume and memory snapshots are listed for VM classes, not the default container class.
• Limits follow your tier. Per-sandbox CPU, memory and disk caps are set by your organization's tier.
• The MCP server runs locally. Daytona's MCP server is set up per app with daytona mcp init for Claude, Cursor or Windsurf; there is no hosted MCP URL to share across agents.
• Price model. You pay per vCPU-hour ($0.0504), per GiB-hour of memory ($0.0162) and for storage, with $200 of free compute to start (pricing).

None of these make Daytona a poor choice. They matter only if they touch your use case.

The 8 best Daytona alternatives for AI agents

1. Simular Box: when you need a computer, not a sandbox

Many teams reach for Daytona to give an agent "a computer." If the agent is one you already use, such as Claude Code, Codex, Cursor or ChatGPT, you may not need an SDK at all. Simular Box (box by Simular) is a cloud computer those agents share through one remote MCP server. Each box is a Linux desktop in the cloud with Chrome, files and a terminal.

• No integration code. Add box to each app once and sign in; the agent gets tools to run commands, browse, click, type and see the screen.
• Shared state. Files, installed apps and signed-in browser sessions stay on the box. Claude can start a task and Codex can finish it; agents take turns on the box.
• People stay in the loop. Watch the box live and take over for a sign-in or 2FA, then hand back.
• Pricing: $5 of free credit once per account; Small $19 a month (4 vCPU / 8 GB, sleeps when idle); Medium $39 a month (never sleeps); extra boxes $0.10 to $0.20 an hour, billed while awake.

Not the right fit when you need thousands of short-lived, isolated runs from code, GPUs, or Windows and macOS. That is what the platforms below are for. For the full trade-off, see sandbox AI vs a cloud computer.

2. E2B: the closest drop-in for code execution

E2B runs isolated sandboxes for agent code, with Python and JavaScript SDKs, a code interpreter, a desktop template for computer use, and pause and resume.

• Pricing: Hobby is free with a one-time $100 usage credit, sessions up to 1 hour and 10 concurrent sandboxes. Pro is $150 a month plus usage, with sessions up to 24 hours and 100 concurrent sandboxes. Usage is billed per second; 1 vCPU costs $0.000014 a second.
• Watch out for: no GPUs; multi-day sessions and BYOC are Enterprise features.

More options in this space: E2B alternatives for AI agents.

3. Modal: sandboxes next to GPUs

Modal Sandboxes run untrusted code, coding agents and RL rollouts on the same platform as Modal's GPU functions, with gVisor or VM runtimes.

• Pricing: per second. Sandboxes bill at non-preemptible rates: $0.00003942 per physical core (2 vCPU) per second and $0.00000667 per GiB of memory per second; GPUs at standard rates.
• Watch out for: a sandbox lives 5 minutes by default and at most 24 hours; longer work uses filesystem snapshots to continue in a new sandbox.

4. Vercel Sandbox: for agents that build web apps

Vercel Sandbox runs each sandbox in a Firecracker microVM with its own filesystem and network, with snapshots and drives. It suits agents that install packages, start a dev server and share a preview.

• Pricing: $0.128 per active CPU-hour and $0.0212 per GB-hour of provisioned memory. Hobby includes 5 active CPU-hours a month.
• Watch out for: sessions last up to 45 minutes on Hobby and 24 hours on Pro.

5. Fly.io Sprites: persistent Linux computers for agents

Sprites are full Linux computers from Fly.io that keep their disk, checkpoint and restore, and sleep until needed. Each gets an HTTPS URL, and Fly.io ships plugins for coding agents.

• Pricing: on actual use: $0.0385 per CPU-hour, $0.021875 per GB-hour of RAM, about $0.50 per GB-month of hot storage.
• Watch out for: no GPU and no desktop for computer use.

6. Northflank: sandboxes in your own cloud

Northflank runs sandboxes alongside services, jobs and databases, on Northflank's cloud or in your own (BYOC).

• Pricing: a free tier with up to $20 a month of resources; pay as you go from $0.01667 per vCPU-hour and $0.00833 per GB-hour; GPUs such as an NVIDIA L4 at $0.80 an hour.
• Watch out for: a full platform with more concepts to learn than a single sandbox API.

7. Cloudflare Sandboxes: code execution beside Workers

Cloudflare Sandboxes run untrusted or generated code from a Worker, with commands, files, preview URLs, terminals and backups to R2.

• Pricing: needs the Workers Paid plan; usage is billed through Containers, Workers and Durable Objects.
• Watch out for: best when your app already runs on Workers; some workspace save features are in beta.

8. Upstash Box: a box with coding agents built in

Upstash Box is a persistent cloud computer with coding agents (Claude Code, Codex, OpenCode) built in, a browser and a repository, controlled through an API or the Upstash MCP server.

• Pricing: pay as you go at $0.10 per active CPU-hour (2 vCPU, 4 GB, 10 GB storage), or a fixed always-on box at $8 a month. Free includes 5 CPU-hours a month.
• Watch out for: no GPU, and storage per box is capped at 10 GB.

How to choose a Daytona alternative for AI agents

• You run agent code from your own product and want the nearest match: E2B
• Your agents need GPUs: Modal, Northflank, or stay on Daytona
• Your stack is on Vercel or Cloudflare: Vercel Sandbox or Cloudflare Sandboxes
• You want each agent to have a persistent Linux machine: Fly.io Sprites or Upstash Box
• You must run in your own cloud: Northflank
• Your agents are Claude Code, Codex, Cursor or ChatGPT and need one shared computer with a browser: Simular Box

Moving off Daytona

• Sandbox create and exec map to Sandbox.create() and command APIs in E2B, Modal and Vercel Sandbox.
• Snapshots and volumes map to E2B templates and pause, Modal filesystem snapshots and volumes, and Vercel snapshots and drives.
• Computer use: E2B has a desktop template; Simular Box gives agents a full desktop through MCP.
• MCP: if your agents used Daytona's local MCP, a hosted server such as box's needs no per-app CLI.

When to stay on Daytona

Stay if you need Windows or macOS sandboxes, a range of GPUs from one API, VM forking with memory snapshots, or SDKs in Ruby, Go or Java. Our Orgo vs E2B vs Daytona vs Simular Box comparison covers those strengths in detail.

More questions

Can any Daytona alternative run Windows or macOS? Among the options here, no. Daytona remains the choice for Windows and macOS sandboxes.

Daytona vs E2B: what is the difference? Both run agent code from SDKs. Daytona adds VM classes, GPUs, Windows and macOS; E2B focuses on fast code execution with pause and resume.

Sources

• Daytona sandboxes, limits, MCP and pricing
• daytonaio/daytona on GitHub
• Tech.eu: Daytona raises $24M Series A
• E2B pricing and persistence
• Modal pricing and Sandboxes guide
• Vercel Sandbox and pricing
• Fly.io Sprites
• Northflank pricing
• Cloudflare Sandboxes and pricing
• Upstash Box and pricing
• Simular Box docs

Prices, limits and features were checked on each vendor's site on November 13, 2026.