10 Best Sandbox Runners in 2025

Running code in production can be risky if something goes wrong. Sandbox runners solve this by giving you a safe, isolated place to run and test code. If you’re building AI agents, running user-generated code, or testing applications, a good sandbox runner keeps things secure without slowing everything down.

But with so many tools out there, choosing the right one can be hard. This guide walks through some of the best sandbox runners to help you pick the right fit for your development workflow.

What is a sandbox runner?

A sandbox runner is a separate, secure environment where you can run code without affecting your main system or other processes. It creates a protective barrier around the code so it can’t access sensitive data or interfere with other apps.

Sandbox runners are especially useful when you need to:

• Run code submitted by users
• Test scripts you don’t fully trust
• Build or run AI coding agents
• Try experimental features without risking production systems

Factors to consider when choosing a sandbox runner

Before looking at specific tools, it helps to know what actually matters when picking a sandbox runner for your use case.

Isolation and security

The main job of any sandbox is to keep things safe. Your sandbox runner should clearly separate the code it runs from the main system. Look for things like containers, virtual machines, or microVMs that make it hard for code to “escape” its sandbox. It should also limit access to important resources like the file system, network, and system calls.

Performance and speed

Sandboxes always add some overhead, but good ones keep it small. Check how fast environments start, how quickly they run code, and whether they support tricks like snapshots to speed up startup time. For production apps, performance can be the difference between a smooth experience and annoying slowdowns.

Language and runtime support

Make sure the sandbox runner works with the languages and runtimes you actually use. Some tools only support a few languages like JavaScript or Python, while others are more flexible. Think about whether you need custom runtimes, certain language versions, or specific libraries and dependencies.

Scalability and resource management

As your app grows, your sandbox setup needs to grow with it. Look for tools that can run many sandboxes at once, manage resources efficiently, and offer pricing that makes sense as you scale. You should be able to set limits on CPU, memory, and execution time to avoid one job using up everything.

Developer experience and integration

A sandbox runner should be easy for developers to work with. Pay attention to the quality of the API, SDKs, and documentation, and how simple it is to plug into your existing systems. The easier it is to integrate and update, the faster your team can ship.

Observability and debugging

Because sandboxes are isolated, it’s important to have good visibility into what’s happening inside them. Choose a tool that gives you logs, metrics, and debugging options. This really helps when you’re fixing bugs, tracking down errors, or tuning performance.

With these points in mind, we can now look at some of the best sandbox runners available.

1. Daytona

Daytona is a secure platform built for running AI-generated and untrusted code. It spins up sandboxes in milliseconds, which makes it well suited for AI agents, code execution workflows, and safe testing.

It uses microVMs to isolate each sandbox, with configurable CPU, memory, and disk, plus controls for how long a sandbox stays active. You can stop sandboxes to save their state without paying for compute, archive them to cheaper storage, or delete them when you no longer need them.

🌟 Key features

• Instant sandbox creation (millisecond startup)
• MicroVM-based isolation for security
• Customizable resources (vCPU, RAM, disk)
• Automated lifecycle management (auto-stop, auto-archive, auto-delete)
• File system persistence across stop/start cycles
• Snapshot support for environment templates
• Preview URLs for running applications
• Built-in toolbox (file system, Git, process execution, PTY)

➕ Pros

• Exceptionally fast cold starts from warm sandbox pools
• Strong security through microVM isolation
• Flexible resource configuration up to 4 vCPUs, 8GB RAM, 10GB disk
• Intelligent cost optimization with automatic state management
• Supports any language or framework via Docker images
• Can run indefinitely or auto-stop after inactivity
• Archive sandboxes to object storage for cost-effective long-term retention
• $200 in free compute credits included
• Startup program offering up to $50,000 in credits
• Enterprise on-premise deployment available

➖ Cons

• Relatively new platform with growing ecosystem
• Default resource limits may require support contact for higher allocations

💲 Pricing

Daytona uses simple usage-based pricing and does not require a credit card for the free trial. You get $200 in free compute credits to start. A small sandbox with 1 vCPU and 1 GiB of RAM costs about $0.067 per hour while it is running, and when it is stopped you only pay for storage, with archived sandboxes stored even more cheaply. Pricing scales with usage, and startups can apply for up to $50,000 in additional credits.

2. E2B

E2B is an open-source sandbox platform made for AI agents and LLM apps. It runs secure, isolated cloud environments using Firecracker microVMs (the tech behind AWS Lambda), which start in under 200 ms with no cold starts.

🌟 Key features

• Firecracker microVM isolation for security
• Sub-200ms startup with no cold starts
• Support for Python, JavaScript, Ruby, C++, and any Linux-compatible language
• Long-running sandboxes (up to 24 hours on Pro plan)
• Code Interpreter with Python and JavaScript kernels
• File system persistence and file uploads
• Terminal access and browser support
• Custom sandbox templates
• Package installation (pip, npm, apt, etc.)
• WebSocket streaming for real-time output

➕ Pros

• Purpose-built for AI agents and LLM workflows
• Trusted by Fortune 100 companies at scale
• Open-source with active community (9.8k+ GitHub stars)
• Extremely fast startup times with no cold starts
• Strong security through Firecracker microVM isolation
• Supports any language or framework that runs on Linux
• Can customize sandboxes with templates
• Real-time output streaming for better UX
• Integrates with all major LLM providers
• Available as BYOC, on-premise, or self-hosted for enterprises
• Free hobby tier with $100 in usage credits

➖ Cons

• Usage costs can accumulate for high-volume applications
• Free tier limited to 1-hour sessions and 20 concurrent sandboxes

💲 Pricing

E2B has three main pricing tiers: a Hobby plan that is free and includes a one-time $100 usage credit, community support, up to 1-hour sessions, and 20 concurrent sandboxes with no credit card required; a Pro plan at $150/month with longer 24-hour sessions, more concurrent sandboxes, and customizable CPU and RAM; and an Enterprise plan with custom pricing, BYOC, on-prem, or self-hosted options.

Usage is billed per second, with RAM included in the CPU price, so a 1 vCPU sandbox costs about $0.05 per hour and you only pay for the time your code is actually running.

3. Cloudflare Workers

Cloudflare Workers runs code using V8 isolates instead of containers or virtual machines. This lets your code start almost instantly and run close to users across 330+ cities worldwide.

Workers run on Cloudflare’s global network, which handles a huge share of Internet traffic and keeps your code within about 50 ms of most users. This makes it a strong fit for apps that need very low latency.

🌟 Key features

• V8 isolate-based sandboxing
• Sub-millisecond cold starts
• Global deployment across 330+ cities
• JavaScript, TypeScript, Python, Rust, and WebAssembly support
• CPU-time billing (not wall-clock time)
• Built-in integrations (KV, R2, D1, Durable Objects)
• Scheduled execution (Cron Triggers)
• WebSocket and real-time communication support
• Browser Rendering for automated browsers
• Workflows for multi-step orchestration

➕ Pros

• Exceptional performance with near-instant cold starts
• Truly global edge network for low-latency worldwide
• Extremely generous free tier (100,000 requests per day)
• Pay only for CPU time, not waiting time
• Integrated ecosystem with storage, databases, and queues
• Scales automatically without configuration
• No DevOps or infrastructure management required
• Compatible with existing frameworks and tools
• Battle-tested infrastructure powering millions of sites
• Predictable pricing without surprise bills

➖ Cons

• V8 isolate restrictions limit some system-level operations
• Default 10ms CPU time limit on free tier may be restrictive
• Better suited for request-response patterns than long-running tasks

💲 Pricing

Cloudflare Workers has a generous free tier with up to 100,000 requests per day and 10 ms of CPU time per request, with no credit card required. The paid plan is usage-based at $0.30 per million requests and $0.02 per million CPU milliseconds, so 1 million requests using 50 ms of CPU each would cost about $1.30 total.

Extra features like Durable Objects, R2, D1, KV, and Workflows are billed separately, and the pay-per-CPU model is very cost-effective for apps with spiky traffic or lots of time waiting on external APIs.

4. Fly.io

Fly.io is a global platform for running full-stack apps and databases close to your users using Firecracker microVMs. It deploys your full app (not just functions) across 35+ regions and routes traffic to the nearest instance.

🌟 Key features

• Firecracker microVM isolation
• Global deployment across 35+ regions
• Any language or framework via Docker
• Built-in managed PostgreSQL and Redis
• Automatic SSL certificates
• Private networking (WireGuard mesh)
• Volume storage for persistent data
• Real-time application scaling
• GPU support (A10, L40S, A100)
• Anycast IPv6 addresses included

➕ Pros

• Full Linux environment with complete control
• Excellent for running complete applications, not just functions
• Fast cold starts (typically under 1 second)
• Strong isolation through Firecracker microVM technology
• Deploy globally with automatic traffic routing
• Can run anything that works in a Docker container
• Built-in database and storage solutions
• Generous free tier includes 3 shared-cpu VMs
• Active community and excellent documentation
• Transparent per-second billing

➖ Cons

• More complex than simpler code execution platforms
• Requires understanding of Docker and deployment concepts
• Costs can accumulate for resource-intensive applications

💲 Pricing

Fly.io has simple usage-based pricing with per-second billing and a small free tier that includes a few VMs, storage, and bandwidth. Paid machines start at just a few dollars per month for small instances, with extra charges for storage, data transfer, GPUs, and add-ons like managed Postgres and Fly Kubernetes. You can also get up to 40% off by buying annual compute credits in advance.

5. Val Town

Val Town lets you write and run TypeScript or JavaScript in the browser with instant execution. Each function you create (a “val”) gets its own API endpoint, so you can quickly build webhooks, cron jobs, and small utilities without managing servers.

It runs on Deno, uses V8 isolates for safe sandboxing, and has a social layer where you can browse, fork, and remix other people’s code. With the built-in AI helper, Val Town is especially useful for fast automations, simple APIs, and custom workflows.

🌟 Key features

• Browser-based code editor with instant deployment
• Automatic API endpoints for every function
• Scheduled execution (cron jobs as fast as 1-minute intervals)
• Built-in blob storage for file uploads and data
• Social features (browse, fork, remix code)
• NPM package support and Deno compatibility
• Built-in secrets management
• AI pair programmer integration
• Custom domain support
• Version control and code intelligence

➕ Pros

• Incredibly fast to go from idea to deployed function (⌘S to deploy)
• No infrastructure management required
• Built on Deno runtime with web standards
• Social features make learning and collaboration easy
• Generous free tier for experimentation
• Automatic HTTPS endpoints for all functions
• Can integrate with thousands of APIs
• Great for automation, bots, and glue code
• Export and run vals in Node.js, Deno, or browsers
• Active community with shared templates

➖ Cons

• Execution time limits can be restrictive for complex tasks
• TypeScript/JavaScript only (no other language support)
• Free tier limited to 5 private vals and 1-minute wall clock time

💲 Pricing

Val Town has four pricing tiers: Free, Pro, Teams, and Enterprise, each with higher limits on runs, runtime, and features like custom domains and collaboration as you move up. The Free plan is generous enough for small projects, while Pro suits most individual developers, and Teams/Enterprise are for larger organizations with higher volume and compliance needs. Yearly billing saves two months and is especially cost-effective if you use Val Town for lots of small utilities and automations.

6. Vercel Sandbox

Vercel Sandbox is an ephemeral compute primitive built for safely running untrusted or user-generated code. It's designed for AI agents, code generation, and developer experimentation, giving you isolated environments to execute third-party code without exposing production systems.

🌟 Key features

• Ephemeral sandboxes for untrusted code execution
• Node.js (node22) and Python (python3.13) runtimes
• Up to 8 vCPUs with 2 GB RAM per vCPU
• Git repository cloning and package installation
• Up to 4 open ports per sandbox
• Real-time log streaming
• Sudo access for package management
• Active CPU billing (I/O wait excluded)
• TypeScript and Python SDKs
• CLI for sandbox management

➕ Pros

• Purpose-built for AI agents and code generation workflows
• Only pay for active CPU time, not I/O waiting
• Can clone private repositories and install packages
• Real-time development server support with live previews
• Strong isolation for running untrusted code safely
• Integrates with Vercel's existing authentication (OIDC)
• Generous free tier for hobby projects (5 CPU hours/month)
• Available in Beta on all Vercel plans
• Easy setup with TypeScript and Python SDKs

➖ Cons

• Currently only available in iad1 region
• Limited to Node.js and Python runtimes
• Hobby plan limited to 45-minute max runtime
• Concurrent sandbox limits (10 for Hobby, 2000 for Pro/Enterprise)

💲 Pricing

Vercel Sandbox is available in Beta on all plans with usage-based pricing. The Hobby plan includes 5 CPU hours, 420 GB-hr provisioned memory, 20 GB network bandwidth, and 5,000 sandbox creations per month for free. Pro and Enterprise plans pay $0.128 per CPU hour, $0.0106 per GB-hr of provisioned memory, $0.15 per GB network, and $0.60 per million sandbox creations. Maximum runtime is 45 minutes for Hobby and 5 hours for Pro/Enterprise, with a default of 5 minutes that you can configure.

7. Modal

Modal is an AI infrastructure platform designed for data and machine learning workloads. It provides containerized execution environments that scale from zero to thousands of parallel instances in seconds, making it ideal for inference, training, batch processing, and any workload that needs to run at scale.

🌟 Key features

• Container-based execution with sub-second cold starts
• Elastic GPU scaling (H200, H100, A100, L40S, A10, L4, T4)
• Automatic scaling from 0 to thousands of containers
• Python-first API with decorators
• Scheduled jobs and cron support
• HTTP endpoints and web servers
• Built-in distributed storage layer
• Programmatic sandboxes for untrusted code
• Shareable collaborative notebooks
• Secrets management

➕ Pros

• Exceptional for AI/ML and data workloads
• Simple Python-first API—just add decorators
• Easy access to GPUs for inference and training
• Scales automatically based on workload
• Sub-second cold starts (100x faster than Docker)
• Pay only for actual compute time (CPU cycles)
• Great for batch processing and parallel execution
• Built-in scheduling for periodic tasks
• Unified observability with integrated logging
• $30/month free compute credits
• SOC 2 and HIPAA compliant

➖ Cons

• Limited to Python (though this is by design)
• Pricing can accumulate for GPU-intensive workloads
• Learning curve for understanding optimal patterns

💲 Pricing

Modal uses per-second billing where you pay only for actual compute time. The Starter plan includes $30/month free compute credits with up to 3 workspace seats, 100 containers, 10 GPU concurrency, and community support. The Team plan at $250/month adds $100 in credits, unlimited seats, 1,000 containers, 50 GPU concurrency, and priority support. Enterprise plans offer volume discounts, higher limits, and dedicated support.

8. CodeSandbox

CodeSandbox is a browser-based development environment built for web development. It uses microVMs to provide full Node.js environments in the cloud, letting you work on complete projects with backend services, databases, and frontend frameworks all running together.

🌟 Key features

• Full-stack development environments
• Real-time collaboration
• MicroVM-based sandboxes and devboxes
• GitHub integration
• Framework templates (React, Vue, Next.js, etc.)
• Built-in terminal and debugging
• Hot reload and instant preview
• CodeSandbox SDK for programmatic management
• Private NPM registry support
• VS Code extension

➕ Pros

• Excellent for web development workflows
• Real-time collaboration features are superb
• Fast environment setup with templates
• Integrates seamlessly with GitHub
• Can run backend services alongside frontend
• Great for teaching and code demonstrations
• No local setup required for contributors
• Built-in browser preview for instant feedback
• SDK enables programmatic environment creation
• Unlimited sandboxes and devboxes on all plans

➖ Cons

• VM credit system can be complex to understand
• Build plan limited to 40 hours of VM credits monthly
• Higher-tier VMs require Pro or Enterprise plans

💲 Pricing

CodeSandbox uses a VM credit system where 1 credit = $0.015. The Build plan is free with 40 hours of monthly VM credits (using Pico VMs), unlimited sandboxes, 5 workspace members, and up to 4 vCPUs + 8GB RAM. The Pro plan at $9/month adds 60 hours of credits, 20 members, and VMs up to 16 vCPUs + 32GB RAM.

9. StackBlitz

StackBlitz created WebContainers, a WebAssembly-based system that runs Node.js directly in your browser. Instead of using remote servers, your whole dev environment runs inside the tab, so it starts instantly and can even work offline.

🌟 Key features

• WebContainer technology (Node.js in browser via WebAssembly)
• Instant environment startup (milliseconds)
• Offline-capable development
• Full npm package support
• Integrated terminal
• Hot reload and fast refresh
• GitHub repository integration
• Framework templates
• Bolt.new AI code generation
• WebContainer API for embedding
• Zero network latency

➕ Pros

• Runs entirely in your browser for privacy and speed
• Instant cold starts with no waiting for servers
• Can continue working offline
• No remote server costs for basic usage
• Excellent for creating bug reproductions
• Great documentation and examples
• Strong integration with popular frameworks
• Secure by default (code doesn't leave your device)
• AI-powered app creation with Bolt.new
• Trusted by major companies (Shopify, Google, etc.)

➖ Cons

• Limited to JavaScript/TypeScript ecosystem
• Complex projects may hit browser resource limits
• WebContainer technology requires modern browsers

💲 Pricing

StackBlitz offers a generous free tier for public projects with full access to WebContainers technology, making it ideal for learning, open-source work, and demonstrations. Paid plans provide private repositories, increased resources, and priority support, with specific pricing available on their website.

10. Replit

Replit is an online IDE and hosting platform that runs in the browser and supports 50+ languages using isolated containers. It is used by millions of developers, from hobbyists to Fortune 500 teams.

🌟 Key features

• 50+ language support
• Browser-based IDE with AI assistance (Replit Agent)
• Real-time collaboration
• Instant hosting and deployment
• Built-in PostgreSQL database
• Package management for all languages
• Always-on deployments
• Mobile app for coding anywhere
• Visual Editor for design refinement
• Autonomous agent that tests its own code
• Figma import capability
• Built-in Auth and Database services

➕ Pros

• Supports more languages than almost any competitor
• Zero setup required to start coding
• Real-time collaboration for pair programming
• Great for learning, prototyping, and production
• Replit Agent dramatically speeds up development
• Can deploy applications directly from the IDE
• Mobile app lets you code from anywhere
• Strong community with 40 million creators
• SOC 2 compliant for enterprise use
• Private deployments for internal tools
• SSO and RBAC for team management

➖ Cons

• Free tier has significant limitations (1200 minutes dev time, public apps only)
• Advanced features require paid plans
• Agent autonomy limited on free tier

💲 Pricing

Replit offers a Starter plan that is free with a Replit Agent trial, 10 development apps with temporary links, public apps only, 1200 minutes of development time, and basic AI features. The Replit Core plan at $20/month includes full Agent access, $25 in monthly credits, unlimited private and public apps, 4 vCPUs, 8 GiB RAM, and advanced AI features.

Final thoughts

In this article, we looked at some of the best sandbox runners available. From AI-focused tools like Daytona and E2B to edge computing with Cloudflare Workers and Vercel Sandbox, plus platforms like Fly.io, Modal, Val Town, CodeSandbox, StackBlitz, and Replit.

Each tool has its strengths, and the right choice depends on your specific needs. I hope this guide helped you pick the best sandbox runner for your project.

Happy coding!

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