--- title: "Best AI Agent Sandbox 2026: E2B vs Daytona vs Modal vs Vercel Sandbox" description: "Where should your AI agent run untrusted code? We compare E2B, Daytona, Modal, Vercel Sandbox, and Cloudflare on cold start, isolation, persistence, GPU support, and real hourly cost." source: https://appstackbuilder.com/blog/best-ai-agent-sandbox-2026 retrieved: 2026-09-21 --- [Back to Blog](https://appstackbuilder.com/blog) AI Infrastructure2026 Guide # Best AI Agent Sandbox 2026 The moment your agent writes code, you have an infrastructure problem: it has to run somewhere that can't hurt you. We compare **E2B, Daytona, Modal, Vercel Sandbox, and Cloudflare** on cold start, isolation model, persistence, GPU support, and what an hour actually costs. 13 min read 5 providers analyzed Published August 2026 ## Quick Verdict ![](https://www.google.com/s2/favicons?domain=e2b.dev&sz=128)E2B Firecracker microVMs — a real kernel boundary per sandbox. \~150ms cold start and the strongest isolation story for untrusted code. Strongest isolation$100 credits ![](https://www.google.com/s2/favicons?domain=daytona.io&sz=128)Daytona Fastest cold start at roughly 90ms, and the only one where sandboxes are _persistent by default_ — a workspace lives until you delete it. Fastest startPersistent ![](https://www.google.com/s2/favicons?domain=modal.com&sz=128)Modal The only one where a sandbox can hold a GPU. If your agent runs inference or fine-tunes inside the sandbox, this is effectively the only option. GPU sandboxesML workloads ![](https://appstackbuilder.com/vercel.svg)Vercel Sandbox Ephemeral by design, billed on _active_ CPU — so I/O wait is free. Unbeatable if you already deploy on Vercel. Ecosystem fitActive-CPU billing ![](https://appstackbuilder.com/cloudflare.svg)Cloudflare Edge-distributed, so the sandbox runs near your user. The trade-off is a 2–3 second cold start — the slowest of the group. EdgeSlow start TL;DR Per-call latency dominates? **Daytona**. Isolation strictness matters most? **E2B**. Workload touches a GPU? **Modal**. Already on Vercel? **Vercel Sandbox**. Need edge distribution? **Cloudflare**. ## Why agents need sandboxes (and why a Docker container isn't one) An AI agent that writes code is, from a security standpoint, an untrusted-code-execution service you built by accident. The model may produce something that reads your environment variables, calls out to the network, forks endlessly, or fills the disk — not because it's adversarial, but because it's probabilistic. And once users can influence the prompt, a prompt injection is a remote code execution vector. The usual first instinct is a Docker container. Containers share the host kernel, so a kernel exploit escapes into the host and into every other container on it. That's an acceptable boundary between _your own_ services and a poor one between you and code a language model just wrote. The providers here solve that with a stronger boundary, and they pick one of two approaches. **microVMs (Firecracker):** each sandbox gets its own Linux kernel via hardware virtualization. This is the strongest boundary available and what E2B is built on. Boot lands around 150ms — slower than a container, but the isolation is real rather than namespaced. **User-space kernels (gVisor):** a software kernel intercepts syscalls before they reach the host. Modal runs on this. Cold starts drop below a second and — critically — GPU passthrough stays straightforward, which hardware virtualization complicates. Once you've picked an isolation model, three questions decide the rest: **how fast** a sandbox starts (agents create them constantly), **how long state survives** (a multi-turn coding session needs the filesystem to persist between tool calls), and **what an hour costs**. ## Platform Overview Five providers optimizing for five different constraints: isolation, speed, GPUs, ecosystem, and edge reach. Strongest Isolation ![](https://www.google.com/s2/favicons?domain=e2b.dev&sz=128) ### E2B Firecracker microVMs for agent code Free + $100 credits Pro $150/mo + usage * ✓Firecracker microVM — own kernel per sandbox * ✓\~150ms cold start * ✓2 vCPU default at $0.000028/second * ✓Memory $0.0000045 per GiB-second * ✓Storage free: 10 GiB Hobby, 20 GiB Pro * ✓Custom templates for preinstalled deps Best for: Agents running genuinely untrusted code where the security boundary is the point Fastest Cold Start ![](https://www.google.com/s2/favicons?domain=daytona.io&sz=128) ### Daytona Sub-90ms persistent workspaces Free + $200 credits usage-based, startups to $50k * ✓Sub-90ms sandbox creation * ✓Persistent by default — lives until deleted * ✓Runs standard Docker/OCI images * ✓First 5 GiB of storage free * ✓$200 free compute on signup * ✓Up to $50k in credits for startups Best for: High-frequency agent loops where per-call startup latency dominates the user experience Only GPU Option ![](https://www.google.com/s2/favicons?domain=modal.com&sz=128) ### Modal gVisor sandboxes that can hold a GPU $0 + $30/mo credits Team $250/mo + $100 credits * ✓The only sandbox that can attach a GPU * ✓gVisor user-space kernel isolation * ✓Sub-second cold starts * ✓CPU $0.0000131/core-second (min 0.125 cores) * ✓H100 $0.001097/s · L4 $0.000222/s · T4 $0.000164/s * ✓Snapshots for warm restore Best for: Agents that run inference, fine-tune, or process media inside the sandbox itself ![](https://appstackbuilder.com/vercel.svg) ### Vercel Sandbox Ephemeral sandboxes, active-CPU billing Free on Hobby $0.128/active CPU-hour on Pro * ✓Billed on active CPU — I/O wait is free * ✓Hobby: 5 CPU-hours + 5,000 creations/month * ✓Memory $0.0212 per GB-hour * ✓Max runtime 45 min Hobby, 24 hr Pro * ✓10 concurrent on Hobby, 10,000 on Pro * ✓Snapshots and persistent sandboxes available Best for: Teams already on Vercel who want sandboxes without adding another vendor ![](https://appstackbuilder.com/cloudflare.svg) ### Cloudflare Sandbox Sandboxes at the edge \~$0.09/hour plus $5/mo Workers base * ✓Runs close to the user, globally distributed * ✓Native fit with Workers and Durable Objects * ✓Predictable flat-ish hourly rate * ✓No egress surprise from the Cloudflare network * ✓Cold start of 2–3 seconds * ✓Limited persistence between runs Best for: Edge-first applications already built on Workers, where locality beats startup speed ### What about just using Docker? Running your own container host is cheaper per hour and entirely reasonable if the code being executed is _yours_. It stops being reasonable the moment a model or a user influences what runs. You would be rebuilding kernel isolation, per-sandbox networking rules, resource caps, filesystem snapshots, and cleanup — which is precisely the list these five providers sell. ## Cost Breakdown (2026) Normalized to a comparable 2 vCPU / 4 GB sandbox running for an hour. Note that these providers meter differently — Vercel bills active CPU only, which changes the math a lot for I/O-heavy agents. ![](https://www.google.com/s2/favicons?domain=e2b.dev&sz=128)E2B Free tier Free + $100 one-time credits Production \~$0.083/hr · Pro $150/mo + usage Session capped at 1 hour (Hobby) or 24 hours (Pro). 20 concurrent sandboxes on Hobby, 100 on Pro, extendable to 1,100. ![](https://www.google.com/s2/favicons?domain=daytona.io&sz=128)Daytona Free tier Free + $200 compute credits Production \~$0.083/hr, usage-based Price parity with E2B but roughly 40% faster cold start. First 5 GiB storage free. Startups can get up to $50k in credits. ![](https://www.google.com/s2/favicons?domain=modal.com&sz=128)Modal Free tier Starter $0 + $30/mo credits Production \~$0.119/hr CPU · GPU billed per second Team plan $250/mo + $100/mo credits, 5,000 containers vs 100 on Starter. GPU is the reason to be here: H100 at $0.001097/s. ![](https://appstackbuilder.com/vercel.svg)Vercel Sandbox Free tier 5 CPU-hrs + 420 GB-hrs/mo on Hobby Production $0.128/active CPU-hr + $0.0212/GB-hr Only active CPU is billed — a 5-min agent task waiting on API calls costs cents. Pro usage draws from the $20/mo credit first. ![](https://appstackbuilder.com/cloudflare.svg)Cloudflare Free tier Requires Workers plan Production \~$0.090/hr + $5/mo base Mid-pack on price, last on cold start. Worth it when running near the user is a product requirement rather than a preference. Rates verified against provider pricing pages as of August 2026\. Hourly figures are normalized estimates for a 2 vCPU / 4 GB sandbox and will differ with your configuration, region, and utilization. **The billing model matters more than the rate.** Agent sandboxes spend most of their life idle — waiting on an LLM call, a package install, or a network request. Vercel bills active CPU only, so that idle time is free. Everyone else bills wall-clock time on provisioned resources. For a chatty agent, that difference can be larger than the headline price gap. ## Feature Comparison Isolation, performance, and operational limits side by side. Feature ![](https://www.google.com/s2/favicons?domain=e2b.dev&sz=128)E2B ![](https://www.google.com/s2/favicons?domain=daytona.io&sz=128)Daytona ![](https://www.google.com/s2/favicons?domain=modal.com&sz=128)Modal ![](https://appstackbuilder.com/vercel.svg)Vercel ![](https://appstackbuilder.com/cloudflare.svg)Cloudflare #### Isolation Isolation model Firecracker microVM gVisor microVM V8 + container Own kernel per sandbox ✓ ✓ user-space ✓ partial Custom images Templates Docker/OCI ✓ ✓ limited #### Performance Cold start \~150ms \~90ms sub-second fast 2–3s GPU in sandbox ✗ ✗ ✓ ✗ ✗ Snapshots / warm restore Templates ✓ ✓ ✓ ✗ Edge distribution ✗ ✗ ✗ iad1 only ✓ #### Limits & ops Persistent by default ✗ ✓ ✗ ✗ ✗ Max session length 1h / 24h Pro unlimited configurable 45m / 24h Pro varies Concurrency (paid) 100–1,100 custom 5,000 containers 10,000 Workers limits Free credits to start $100 $200 $30/mo Hobby quota ✗ ![](https://www.google.com/s2/favicons?domain=e2b.dev&sz=128) ## Deep Dive: E2B E2B is the security-first answer. Every sandbox is a **Firecracker microVM** with its own Linux kernel, which is the same primitive AWS Lambda uses to separate tenants. That closes the class of cross-tenant escapes that container-based isolation leaves open, at the cost of a \~150ms boot instead of a container's few tens of milliseconds. Pricing is granular and cheap: the default 2 vCPU configuration runs $0.000028/second with memory at $0.0000045 per GiB-second, and storage is included (10 GiB on Hobby, 20 GiB on Pro). Hobby ships **$100 in one-time credits**, which is a lot of sandbox-hours for a prototype. The Pro plan at $150/month lifts sessions from 1 hour to 24 and concurrency from 20 to 100, extendable to 1,100. **Best for:** Agents executing genuinely untrusted code, or anything where you'll be asked to describe the isolation boundary in a security review. **Skip if:** you need a GPU inside the sandbox, or 60ms of extra cold start is user-visible in your loop. ![](https://www.google.com/s2/favicons?domain=daytona.io&sz=128) ## Deep Dive: Daytona Daytona competes on the two things E2B trades away: **speed and persistence**. Sandbox creation lands around 90ms — roughly 40% faster than E2B at essentially identical pricing — and tuned configurations have been measured near 27ms. When an agent creates a fresh sandbox on every tool call, that difference compounds across a session. The bigger architectural difference is that Daytona workspaces are **persistent by default**. E2B and Modal sandboxes are ephemeral things you snapshot to preserve; a Daytona workspace exists until you delete it, more like a Codespace. For long-running agents that revisit the same project across hours or days, that removes an entire category of state-management code. It runs standard Docker/OCI images, so your existing Dockerfile works, and signup includes $200 in compute with up to $50k in credits available to startups. **Best for:** High-frequency agent loops and long-lived coding sessions. **Skip if:** you need GPUs, or your compliance story specifically requires Firecracker. ![](https://www.google.com/s2/favicons?domain=modal.com&sz=128) ## Deep Dive: Modal Modal is the outlier, and the comparison mostly collapses to one fact: it is the only platform where a sandbox can **hold a GPU**. If your agent needs to run inference, fine-tune a model, or process images inside the same isolated process that handles its tool calls, Modal is the option. That capability comes from its isolation choice — gVisor is a software kernel, so GPU passthrough stays straightforward in a way hardware virtualization complicates. CPU runs $0.0000131 per core-second (minimum 0.125 cores) and memory $0.00000222 per GiB-second, with GPUs billed per second: T4 at $0.000164, L4 at $0.000222, H100 at $0.001097, B300 at $0.001972\. The Starter plan is $0 with $30/month in credits and 100 containers; Team is $250/month with $100/month in credits and 5,000 containers. Cold starts are sub-second — slower than Daytona, irrelevant next to the GPU capability. **Best for:** ML-adjacent agents, code interpreters that handle media, anything needing accelerated compute in-sandbox. **Skip if:** you're only running CPU code — you'll pay roughly 40% more per hour than E2B or Daytona for capability you don't use. ![](https://appstackbuilder.com/vercel.svg) ## Deep Dive: Vercel Sandbox Vercel Sandbox wins on two things that don't show up in a cold-start benchmark. First, **active-CPU billing**: time your sandbox spends waiting on I/O — an LLM call, a package install, a database query — isn't billed. For agent workloads, which are overwhelmingly I/O-bound, that can be the single biggest cost lever available. Vercel's own example puts a 5-minute, 2 vCPU AI code-validation run at about $0.03. Second, it's one less vendor. If you're already deploying on [Vercel](https://appstackbuilder.com/blog/vercel-vs-railway-hosting-comparison), sandboxes are one API and one bill. The Hobby tier includes 5 CPU-hours, 420 GB-hours of memory, and 5,000 creations per month free. The constraints to know: maximum runtime is 45 minutes on Hobby (24 hours on Pro), concurrency is 10 on Hobby versus 10,000 on Pro, and — the real limitation — **it currently runs only in the iad1 region**. **Best for:** Teams already on Vercel, and I/O-heavy agents where idle time dominates. **Skip if:** you need multi-region execution or GPU access. ![](https://appstackbuilder.com/cloudflare.svg) ## Deep Dive: Cloudflare Sandbox Cloudflare's pitch is locality: the sandbox runs on the same edge network as your Workers, near the user, with no egress penalty for traffic that stays inside Cloudflare. If your agent already lives in a Worker and coordinates through Durable Objects, keeping execution in the same platform avoids a round trip to a distant region on every tool call. The cost is startup time. A **2–3 second cold start** is an order of magnitude worse than Daytona or E2B, and in an interactive agent loop that is plainly noticeable. At roughly $0.09/hour plus the $5/month Workers base, pricing sits mid-pack — you're paying for distribution, not compute economics. **Best for:** Edge-first apps already built on Workers where geographic locality is a product requirement. **Skip if:** cold start is in your critical path — which, for most agent loops, it is. ## Decision Guide ### Your agent creates sandboxes constantly Use **Daytona**. Sub-90ms creation at the same price as E2B, and persistent workspaces mean you often don't need to recreate at all. ![](https://www.google.com/s2/favicons?domain=daytona.io&sz=128)Daytona ### You're running untrusted or user-influenced code Use **E2B**. Firecracker gives each sandbox its own kernel — the strongest boundary here, and the easiest one to defend in a security review. ![](https://www.google.com/s2/favicons?domain=e2b.dev&sz=128)E2B ### The workload touches a GPU Use **Modal**. It is the only serious option where a sandbox can attach a GPU, billed per second from $0.000164 (T4) to $0.001972 (B300). ![](https://www.google.com/s2/favicons?domain=modal.com&sz=128)Modal ### You're already on Vercel — or your agent waits a lot Use **Vercel Sandbox**. One vendor, one bill, and active-CPU billing means idle time spent waiting on LLM calls costs nothing. ![](https://appstackbuilder.com/vercel.svg)Vercel Sandbox ### Execution needs to happen near the user Use **Cloudflare Sandbox**. Native to Workers and globally distributed — accept the 2–3 second cold start as the price of locality. ![](https://appstackbuilder.com/cloudflare.svg)Cloudflare ## Building an agent product? Get the whole stack Your sandbox is one piece. Use our AI-powered generator to build a complete stack — database, hosting, auth, LLM provider, and more — tailored to your budget and team size. [Generate Your Tech Stack](https://appstackbuilder.com/build-stack?budget=100&appType=ai&teamSize=solo) ## Frequently Asked Questions ### Can't I just run agent code in a Docker container? You can, but containers share the host kernel — a kernel exploit escapes into the host and every other container on it. That's a reasonable boundary between your own services and a weak one between you and code an LLM just wrote. Firecracker microVMs (E2B) or gVisor (Modal) give each sandbox a real kernel boundary. ### E2B vs Daytona: which should I choose? They're at price parity, so it comes down to two things. Choose **Daytona** for speed (\~90ms vs \~150ms cold start) and persistent-by-default workspaces. Choose **E2B** when Firecracker's strict isolation is a requirement you have to document. For most agent products, either is fine — try both against your actual loop. ### Which sandbox supports GPUs? Only **Modal**, among these five. Its gVisor-based isolation keeps GPU passthrough straightforward where hardware virtualization complicates it. GPUs bill per second — T4 $0.000164, L4 $0.000222, H100 $0.001097, B300 $0.001972. ### How long can a sandbox stay alive? It varies a lot. **E2B**: 1 hour on Hobby, 24 hours on Pro. **Vercel**: 45 minutes on Hobby, 24 hours on Pro. **Modal**: configurable, with snapshots for warm restore. **Daytona** is the exception — workspaces are persistent by default and live until you delete them. ### What does a sandbox actually cost to run an AI agent? For a 2 vCPU / 4 GB sandbox, roughly **$0.08–0.15 per hour** of wall-clock time. But agent sandboxes are mostly idle waiting on I/O, so the billing model matters more than the rate — Vercel bills only active CPU, putting a 5-minute code-validation task near $0.03 rather than a full hourly slice. ### Do I need a sandbox if my agent only calls APIs? No. Sandboxes solve _code execution_. If your agent only calls typed tools you wrote — sending email, querying your database, hitting an API — you need good authorization design, not isolation infrastructure. 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