Run concurrent agents
in isolated VMs
Up to 100 sandboxes at once on Pro, or any number on Enterprise. Each boots in under 250 ms.
Give your agent a Cloud VM with a browser and persistent storage. Scale to thousands of sandboxes and ship what agents build in one command.
npx skills add lizard-build/skill -gnpx skills add lizard-build/skill -gcurl -fsSL https://lizard.build/Built for agents. Ready for your product.
Up to 100 sandboxes at once on Pro, or any number on Enterprise. Each boots in under 250 ms.
A volume keeps your files after a sandbox stops. Attach it to your next sandbox to use the same files.
Run web apps your agents build with Managed Postgres, Redis and S3-compatible storage, without managing CI/CD.
Use the built-in desktop and browser to interact with apps in your sandbox and check your agent’s work.
Choose US East or EU West when you create a sandbox.
Read process output and track resource usage to debug errors and identify resource bottlenecks.
Choose your sandbox size and runtime.
Estimate compute costs before subscription fees and credits.
Estimated sandbox costs
$0.71/ month
The hourly rate includes the CPU, RAM and local disk shown above. A running sandbox is billed even while idle; pausing it stops its compute charge. Persistent Volumes continue to accrue storage charges.
This estimate covers sandbox compute only. Pro subscription fees, monthly credits and trial credits are not included.
Trial accounts can run up to 5 Sandboxes at once; Pro supports up to 100. Higher limits need an agreement. Restored or legacy resources may use a different billing model.
Full pricing & billing details ↗Price per hour for 2 vCPU and 4 GB of memory, from each provider's public pricing page. Rates checked on .
| Provider | Per hour | Compared with Lizard | How it is billed |
|---|---|---|---|
| Lizard | $0.0162 | 1× | Flat rate per size, billed by the second |
| Cloudflare | $0.0697 | 4.3× | 10% active CPU; memory and disk as provisioned |
| Vercel | $0.1104 | 6.8× | 10% active CPU; all allocated memory |
| E2B | $0.1656 | 10× | Per vCPU and GiB of memory, by the second |
| Daytona | $0.1656 | 10× | Per vCPU and GiB of memory, by the second |
| Modal | $0.2380 | 15× | Sandbox rates; 1 physical core = 2 vCPU |
Vercel and Cloudflare bill CPU only while it is active, so the table assumes 10% active CPU, as the calculator does. Plan fees, credits, storage and egress are not included.
Lowest median. Lowest average. Measured against E2B, Daytona, and Modal.
Lowest median time
| Provider | Median | Average | p90 | p95 | p99 | Maximum |
|---|---|---|---|---|---|---|
| Lizard | 228 ms — Lowest time | 239 ms — Lowest time | 265 ms — Lowest time | 310 ms — Lowest time | 477 ms — Lowest time | 693 ms — Lowest time |
| E2B | 264 ms | 323 ms | 487 ms | 603 ms | 736 ms | 1,260 ms |
| Daytona | 819 ms | 945 ms | 1,370 ms | 1,671 ms | 2,332 ms | 5,532 ms |
| Modal | 929 ms | 983 ms | 1,290 ms | 1,422 ms | 1,593 ms | 1,932 ms |
· 300 starts per provider, from the create request to the first verified Python output. Runner: Railway US East (us-east4).
Lizard: base template, Small (2 vCPU / 4 GB), us-east-1. Providers used different regions, templates and resource sizes. Starts can use prepared capacity; results vary by workload.
Create a Firecracker microVM, run a command and stop it with Lizard SDK for TypeScript and Python, or with Lizard CLI.
npm install @lizard-build/sdkimport { Lizard } from '@lizard-build/sdk'// Reads LIZARD_API_KEY from the environmentconst lizard = new Lizard({ project: 'my-project' })const sandbox = await lizard.create('interpreter', { size: 'small' })try { const run = await sandbox.process.exec("python -c 'print(2 ** 10)'") console.log(run.stdout) // 1024} finally { await sandbox.kill()}pip install lizard-sdkfrom lizard import Lizard# Reads LIZARD_API_KEY from the environmentlizard = Lizard(project="my-project")with lizard.create("interpreter", size="small") as sandbox: run = sandbox.process.exec_("python -c 'print(2 ** 10)'") print(run.stdout) # 1024curl -fsSL https://lizard.build/install.sh | bashlizard sandbox create -t interpreter -s small # prints the sandbox IDlizard sandbox exec <sandbox-id> -- python -c 'print(2 ** 10)'lizard sandbox rm <sandbox-id> -yAn AI sandbox is a separate place for an agent to run code, use tools, and work with files. Lizard Sandboxes let agents build, test, and debug in the cloud without running that code on your computer.
Sign in to Lizard, choose a project, and create a sandbox from a ready-made template. Choose base for shell tasks, codex for coding tasks, or interpreter for Python, then select a size and region.
Yes. Run Python scripts with the interpreter template, or use shell commands to run tools and tests. Read command output and save results to files. Each command starts a new process.
In our 12 October 2026 test, the median time from the create request to the first Python output was 228 ms over 300 starts (base template, Small size, us-east-1). E2B took 264 ms, Daytona 819 ms and Modal 929 ms in the same test. Results vary with the template, size, region and free capacity.
Lizard Sandboxes run as Firecracker microVMs, each with its own kernel. Give the agent only the credentials and access its task needs.
You choose the lifetime when creating a sandbox, including no automatic expiry for longer tasks. A sandbox stops at its deadline even if a command is running. Commands do not extend the deadline, and idle time does not stop it early.
Yes. Attach Persistent Volumes at /workspace to keep files after a sandbox stops and reuse them in later runs. A volume connects to one sandbox at a time. Storage stays on one node, so export files you need to protect against node loss.
Yes. With access to your project, an agent can deploy apps and databases through Lizard CLI. They run as separate resources on Lizard and keep running after you stop or delete the sandbox.
Yes. Create a separate sandbox for each task so agents can run commands and tests at the same time. The trial runs up to 5 Sandboxes at once and Pro up to 100. Enterprise has no limit on how many run at once, so you can scale to thousands.
The Small size costs $0.0162/hour for 2 vCPU and 4 GB RAM. For the same 2 vCPU and 4 GB, E2B and Daytona charge $0.1656/hour and Modal $0.2380/hour (rates checked on 20 October 2026). Billing runs by the second while the sandbox runs, including idle time. CPU and RAM are included, along with 2 TB of sandbox egress per account over a rolling 30 days. A successful pause stops compute charges; Persistent Volumes storage is billed separately. Older sandboxes without a size keep their original usage-based billing.
Sandbox egress limitsYes. Pro starts with a 7-day trial and $5 in trial credits, and Sandboxes run on it, up to 5 at once. You need a card to start, and we charge nothing during the trial. After it, Pro costs $19/month with $19 in monthly credits included. Once you use your credits, pay as you go.
Create a sandbox, run a command, then pick a guide for your agent.
Create a sandbox, run Python and open a port with Lizard SDK.
You don't need a platform team to go live. Your whole cloud, one CLI command away.