CodeSandbox Pricing & Plans 2026

Name: CodeSandbox
Brand: CodeSandbox
Availability: InStock

Complete pricing guide for CodeSandbox. Compare all plans, analyze costs, and find the perfect tier for your needs.

Not sure if free is enough? See our Free vs Paid comparison →
Still deciding? Read our full verdict on whether CodeSandbox is worth it →

🆓Free Tier Available

💎4 Paid Plans

⚡No Setup Fees

Choose Your Plan

Free

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Pro

$9/month per user

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Team

$20/month per user

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Sandbox SDK / Enterprise

Usage-based, ~$0.005/VM-minute; custom enterprise pricing

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Pricing sourced from CodeSandbox · Last verified March 2026

Feature Comparison

Detailed feature comparison coming soon. Visit CodeSandbox's website for complete plan details.

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Is CodeSandbox Worth It?

✅ Why Choose CodeSandbox

• Firecracker microVM snapshots resume environments in roughly 2 seconds, eliminating cold-start dependency installs and rebuild times on reopen
• Environment branching forks the entire VM state — running processes, installed packages, open ports — so agents or developers can explore parallel changes without re-bootstrapping
• Sandbox SDK exposes the same microVM infrastructure programmatically via Node.js and Python, enabling AI agents to spawn isolated execution environments at runtime
• Real-time multiplayer editing with live cursors, shared terminals, and shared port previews works without configuration, similar to Google Docs for code
• Kernel-level VM isolation (not shared containers) provides stronger security boundaries when executing untrusted or LLM-generated code than typical sandboxing
• Works across browser, VS Code extension, and JetBrains IDEs with bidirectional GitHub sync, so teams aren't forced into a single editor

⚠️ Consider This

• Free tier credits are consumed by VM runtime hours and are easy to exhaust on long-running backend or full-stack projects, pushing teams to paid plans quickly
• GPU workloads and heavy ML training are not first-class — the platform is optimized for general dev environments and agent code execution, not CUDA-bound tasks
• Performance for very large monorepos can lag behind a local machine because file system operations route through the remote VM and editor over the network
• Sandbox SDK pricing scales with concurrent VMs and runtime, which can become expensive for high-volume agent products compared to lighter container-based runners like E2B
• Browser-only editing has limitations (extension ecosystem, keybinding quirks, offline use) that make it less attractive than running VS Code or JetBrains locally for some workflows

What Users Say About CodeSandbox

👍 What Users Love

✓Firecracker microVM snapshots resume environments in roughly 2 seconds, eliminating cold-start dependency installs and rebuild times on reopen
✓Environment branching forks the entire VM state — running processes, installed packages, open ports — so agents or developers can explore parallel changes without re-bootstrapping
✓Sandbox SDK exposes the same microVM infrastructure programmatically via Node.js and Python, enabling AI agents to spawn isolated execution environments at runtime
✓Real-time multiplayer editing with live cursors, shared terminals, and shared port previews works without configuration, similar to Google Docs for code
✓Kernel-level VM isolation (not shared containers) provides stronger security boundaries when executing untrusted or LLM-generated code than typical sandboxing
✓Works across browser, VS Code extension, and JetBrains IDEs with bidirectional GitHub sync, so teams aren't forced into a single editor

👎 Common Concerns

⚠Free tier credits are consumed by VM runtime hours and are easy to exhaust on long-running backend or full-stack projects, pushing teams to paid plans quickly
⚠GPU workloads and heavy ML training are not first-class — the platform is optimized for general dev environments and agent code execution, not CUDA-bound tasks
⚠Performance for very large monorepos can lag behind a local machine because file system operations route through the remote VM and editor over the network
⚠Sandbox SDK pricing scales with concurrent VMs and runtime, which can become expensive for high-volume agent products compared to lighter container-based runners like E2B
⚠Browser-only editing has limitations (extension ecosystem, keybinding quirks, offline use) that make it less attractive than running VS Code or JetBrains locally for some workflows

Pricing FAQ

How does CodeSandbox achieve 2-second startup times?

CodeSandbox runs each project inside a Firecracker microVM and snapshots the full VM state — memory, running processes, open ports, and installed dependencies — to disk. When you reopen a sandbox, the platform restores from the snapshot instead of cold-booting and reinstalling, so your dev server, database, and build tools resume in roughly two seconds.

What is the Sandbox SDK and who is it for?

The Sandbox SDK is a Node.js and Python library that lets developers programmatically create, fork, and destroy CodeSandbox microVMs from their own applications. It's primarily aimed at AI product teams that need to execute LLM-generated code in isolated environments — for example, coding agents, data-analysis copilots, or interactive tutorials — and want kernel-level VM isolation rather than shared-container sandboxing.

How does CodeSandbox compare to GitHub Codespaces and Gitpod?

Codespaces and Gitpod use container-based dev environments with cold starts measured in tens of seconds to minutes. CodeSandbox uses snapshotted Firecracker microVMs that resume in seconds and supports environment branching (forking a running VM). It also offers a programmatic SDK for agent use cases, which Codespaces and Gitpod do not natively expose.

Can I use my own VS Code or JetBrains IDE with CodeSandbox?

Yes. CodeSandbox provides a VS Code extension and JetBrains plugin (Cloud Containers) that connect your local IDE to a remote microVM. You get the same microVM infrastructure and real-time collaboration features while keeping your local extensions, keybindings, and editor configuration.

Is CodeSandbox safe for running untrusted or AI-generated code?

CodeSandbox isolates each sandbox in its own Firecracker microVM with a separate kernel, which is a stronger boundary than the shared-kernel containers used by many code-execution services. This makes it a common choice for AI products that need to execute model-generated code on behalf of end users without exposing the host environment.

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CodeSandbox Pricing & Plans 2026

Complete pricing guide for CodeSandbox. Compare all plans, analyze costs, and find the perfect tier for your needs.

🆓Free Tier Available

💎4 Paid Plans

⚡No Setup Fees

Is CodeSandbox Worth It?

✅ Why Choose CodeSandbox

• Firecracker microVM snapshots resume environments in roughly 2 seconds, eliminating cold-start dependency installs and rebuild times on reopen
• Environment branching forks the entire VM state — running processes, installed packages, open ports — so agents or developers can explore parallel changes without re-bootstrapping
• Sandbox SDK exposes the same microVM infrastructure programmatically via Node.js and Python, enabling AI agents to spawn isolated execution environments at runtime
• Real-time multiplayer editing with live cursors, shared terminals, and shared port previews works without configuration, similar to Google Docs for code
• Kernel-level VM isolation (not shared containers) provides stronger security boundaries when executing untrusted or LLM-generated code than typical sandboxing
• Works across browser, VS Code extension, and JetBrains IDEs with bidirectional GitHub sync, so teams aren't forced into a single editor

⚠️ Consider This

• Free tier credits are consumed by VM runtime hours and are easy to exhaust on long-running backend or full-stack projects, pushing teams to paid plans quickly
• GPU workloads and heavy ML training are not first-class — the platform is optimized for general dev environments and agent code execution, not CUDA-bound tasks
• Performance for very large monorepos can lag behind a local machine because file system operations route through the remote VM and editor over the network
• Sandbox SDK pricing scales with concurrent VMs and runtime, which can become expensive for high-volume agent products compared to lighter container-based runners like E2B
• Browser-only editing has limitations (extension ecosystem, keybinding quirks, offline use) that make it less attractive than running VS Code or JetBrains locally for some workflows

What Users Say About CodeSandbox

👍 What Users Love

✓Firecracker microVM snapshots resume environments in roughly 2 seconds, eliminating cold-start dependency installs and rebuild times on reopen
✓Environment branching forks the entire VM state — running processes, installed packages, open ports — so agents or developers can explore parallel changes without re-bootstrapping
✓Sandbox SDK exposes the same microVM infrastructure programmatically via Node.js and Python, enabling AI agents to spawn isolated execution environments at runtime
✓Real-time multiplayer editing with live cursors, shared terminals, and shared port previews works without configuration, similar to Google Docs for code
✓Kernel-level VM isolation (not shared containers) provides stronger security boundaries when executing untrusted or LLM-generated code than typical sandboxing
✓Works across browser, VS Code extension, and JetBrains IDEs with bidirectional GitHub sync, so teams aren't forced into a single editor

👎 Common Concerns

⚠Free tier credits are consumed by VM runtime hours and are easy to exhaust on long-running backend or full-stack projects, pushing teams to paid plans quickly
⚠GPU workloads and heavy ML training are not first-class — the platform is optimized for general dev environments and agent code execution, not CUDA-bound tasks
⚠Performance for very large monorepos can lag behind a local machine because file system operations route through the remote VM and editor over the network
⚠Sandbox SDK pricing scales with concurrent VMs and runtime, which can become expensive for high-volume agent products compared to lighter container-based runners like E2B
⚠Browser-only editing has limitations (extension ecosystem, keybinding quirks, offline use) that make it less attractive than running VS Code or JetBrains locally for some workflows