E2B vs Vercel Sandbox
Compare E2B and Vercel Sandbox by workflow, pricing, privacy, model support, and best use cases.
E2B
Choose E2B when you are building AI agents, code interpreters, browser/computer-use agents, or LLM applications that need secure, fast, isolated code execution. Choose GitHub Codespaces, Gitpod/Ona, or Coder for full developer workspaces, CodeSandbox for collaborative cloud sandboxes, or Daytona/Vercel Sandbox when their pricing, lifecycle, or platform fit is better for your agent runtime.
Vercel Sandbox
Choose Vercel Sandbox when you are building Vercel-hosted AI apps or agent workflows that need safe, ephemeral execution of generated code. Choose E2B or Daytona for more dedicated provider-neutral AI sandbox infrastructure, GitHub Codespaces or Coder for full developer workspaces, and StackBlitz for browser-native web development.
Key Differences
Workflow
E2B is an open-source AI sandbox cloud for giving agents secure, isolated computers where they can execute code, use tools, and run workflows.
Vercel Sandbox is a Vercel-native isolated compute primitive for safely executing generated or untrusted code in AI apps, agent workflows, and developer platforms.
compare.fields.openSource
Yes
No
Feature Comparison
| Feature | E2B | Vercel Sandbox |
|---|---|---|
| Primary workflow | E2B is an open-source AI sandbox cloud for giving agents secure, isolated computers where they can execute code, use tools, and run workflows. | Vercel Sandbox is a Vercel-native isolated compute primitive for safely executing generated or untrusted code in AI apps, agent workflows, and developer platforms. |
| Type | resource | resource |
| Editor base | CLI | CLI |
| Pricing model | freemium | freemium |
| Starting price | $0 | $0 |
| Free plan | Yes | Yes |
| Open source | Yes | No |
| Local models | No | No |
| BYOK | No | No |
| Platforms | Cloud sandboxes, JavaScript SDK, TypeScript SDK, Python SDK, REST API, CLI, GitHub Actions, MCP Gateway, Docker MCP Catalog, Cloud browser, Desktop sandbox, Linux microVMs, Custom sandbox templates | Vercel, Next.js, Vercel AI SDK, Vercel Functions, Vercel AI Cloud, Node.js runtime, Python runtime, Sandbox SDK, Sandbox CLI, Amazon Linux 2023 |
| Models | Unknown | Unknown |
| Enterprise features | Custom pricing, Custom concurrency above 1,100 sandboxes, Custom CPU and memory ceilings, Higher disk limits, Custom continuous runtime, Enterprise support, Bring Your Own Cloud documentation path, Security review, Trust Center, Lifecycle webhooks, Metrics, OpenTelemetry export, Custom templates, Private registries, Custom MCP servers, MCP Gateway, Sandbox public URL controls, Proxy tunneling, Custom domains, Secured access | Enterprise Vercel plan support, Custom Vercel contracts, Higher-scale usage discussions, Team-level billing and usage controls, Vercel platform security controls, Vercel organization governance, Enterprise support, Vercel AI Cloud integration, Usage observability through Vercel billing, Higher paid concurrency limits |
| Best for | AI agent code execution, Code interpreter products, Running untrusted AI-generated code, LLM tool execution, Data analysis agents, Coding agents that need terminal and filesystem access, Computer-use agents, Cloud browser workflows, MCP-enabled agent tools, GitHub Actions validation, Sandboxed test runners, Products that need fast isolated execution environments | AI-generated code execution, Next.js AI apps, Vercel-hosted agent workflows, Code interpreter features, Dynamic Python execution, Data processing inside AI apps, Running untrusted user code, Evaluation sandboxes, Interactive app playgrounds, Agentic web applications, Vercel AI SDK tools, Teams already deploying on Vercel |
| Not best for | Developers looking for a complete cloud IDE, Non-technical users looking for prompt-to-app builders, Teams that only need simple frontend playgrounds, Projects that require fixed monthly pricing with no usage metering, Workflows where agents do not need to execute code, Organizations unwilling to manage sandbox permissions, secrets, and network policies | Developers looking for a full browser IDE, Teams needing self-hosted sandbox infrastructure, Provider-neutral agent platforms, Long-lived development workspaces, Workloads requiring arbitrary VM images or full operating-system control, Teams that need local model execution, Non-technical users looking for prompt-to-app builders |
Use Case Winners
Vercel Sandbox is built around a CLI editor workflow.
Both E2B and Vercel Sandbox have comparable signals here.
E2B lists more team or enterprise controls.
Both E2B and Vercel Sandbox have comparable signals here.
Neither tool shows a strong signal for this use case in the current structured data.
E2B is marked as open source.
Pricing Comparison
E2B
- Hobby$0 / month
Free plan with one-time $100 usage credits, community support, up to 1-hour sandbox sessions, and up to 20 concurrent sandboxes.
- Pro$150 / month
Adds higher limits, custom sandbox CPU and RAM, up to 24-hour sessions, up to 100 concurrent sandboxes, and optional extra concurrency up to 1,100.
- EnterpriseCustom
Custom pricing, higher limits, custom compute, 1,100+ concurrent sandboxes, and enterprise deployment or support discussions.
- Compute usageFrom $0.000014 / vCPU-second
Usage-based compute billing while sandboxes are running. Default 2 vCPU costs $0.000028/second.
- Memory usage$0.0000045 / GiB-second
Memory is billed per GiB-second while a sandbox is actively running.
Vercel Sandbox
- Hobby Included Usage$0 / month
Includes limited monthly Sandbox usage such as 5 active CPU hours, 420 GB-hours memory, 5,000 creations, 20 GB transfer, 15 GB lifetime storage, and 10 concurrent sandboxes.
- Pro / Enterprise Active CPU$0.128 / hour
Usage-based Sandbox active CPU billing on paid Vercel plans.
- Pro / Enterprise Memory$0.0424 / GB-hour
Provisioned Sandbox memory billing on paid Vercel plans.
- Sandbox Creations$0.60 / 1M creations
Usage-based billing for creating Sandbox instances after included Hobby usage.
- Data Transfer$0.15 / GB
Usage-based data transfer pricing after included Hobby allowance.
Privacy & Security
E2B
E2B sandboxes can contain AI-generated code, uploaded files, command output, environment variables, MCP tool results, browser activity, Git context, and persistent filesystem or memory state. Teams should avoid placing production secrets directly into generated code or broad sandbox environments, restrict network and MCP tool access, review custom templates, use lifecycle controls to pause or kill idle sandboxes, and define retention policies for snapshots, files, logs, and agent outputs.
Vercel Sandbox
Vercel Sandbox may execute user-generated or AI-generated code, filesystem content, runtime logs, command output, data files, dependencies, and application-provided inputs inside ephemeral Vercel-managed environments. Teams should avoid passing production secrets or regulated data into sandboxes unless they have reviewed access controls, retention behavior, logging, network exposure, file persistence, public URLs, and organization-level Vercel security settings.
Choose E2B if...
- AI agent code execution
- Code interpreter products
- Running untrusted AI-generated code
- LLM tool execution
- Data analysis agents
Choose Vercel Sandbox if...
- AI-generated code execution
- Next.js AI apps
- Vercel-hosted agent workflows
- Code interpreter features
- Dynamic Python execution
Avoid E2B if...
- Developers looking for a complete cloud IDE
- Non-technical users looking for prompt-to-app builders
- Teams that only need simple frontend playgrounds
- Projects that require fixed monthly pricing with no usage metering
- Workflows where agents do not need to execute code
Avoid Vercel Sandbox if...
- Developers looking for a full browser IDE
- Teams needing self-hosted sandbox infrastructure
- Provider-neutral agent platforms
- Long-lived development workspaces
- Workloads requiring arbitrary VM images or full operating-system control