E2B vs Daytona

Detailed side-by-side comparison to help you choose the right tool

E2B

🔴Developer

AI Infrastructure & Sandboxes

Secure cloud sandboxes that let AI agents run untrusted code, install packages, and execute long-running tasks in isolated micro-VMs.

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Starting Price

Free

Daytona

🔴Developer

AI Infrastructure & Training

Open-source sandbox infrastructure for running AI-generated code safely. Sub-90ms startup, per-second billing, and stateful environments for AI agents and code interpreters.

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Starting Price

$0.0504/hr per vCPU

Feature Comparison

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FeatureE2BDaytona
CategoryAI Infrastructure & SandboxesAI Infrastructure & Training
Pricing Plans70 tiers8 tiers
Starting PriceFree$0.0504/hr per vCPU
Key Features
  • Hardware-level security isolation
  • Sub-150ms sandbox startup
  • Multi-language runtime support

    E2B - Pros & Cons

    Pros

    • Strong isolation via Firecracker — safe enough for fully LLM-generated code
    • 150ms cold-start is fast enough for interactive chat-style agents
    • Drop-in ChatGPT-style Code Interpreter SDK with persistent Jupyter kernels
    • Desktop sandbox makes browser-use and computer-use agents practical
    • Production-proven (Perplexity, Hugging Face) and well-instrumented

    Cons

    • Per-hour pricing can balloon for long-running autonomous agents
    • Pro tier only includes 20 hours/mo — most teams burn through it
    • Smaller per-sandbox resource limits than running on your own GPU box
    • No GPU access on standard sandboxes (use Modal or RunPod for that)

    Daytona - Pros & Cons

    Pros

    • Sub-90ms sandbox startup is the fastest in the AI code execution space
    • Per-second billing means you pay only for actual compute time, not rounded-up minutes
    • $200 in free credits is generous enough to build and test a full agent workflow before spending anything
    • Stateful environments save time on multi-step agent tasks that need package installation and file persistence
    • Open-source core lets you self-host for full control over data and costs
    • MCP server support simplifies integration with modern AI agent frameworks

    Cons

    • GPU pricing ($0.014/second = ~$50/hour) gets expensive fast for sustained ML workloads
    • Newer platform than E2B with a smaller ecosystem of examples and community resources
    • Enterprise and on-premise features require sales engagement with no public pricing
    • Documentation is functional but thinner than established competitors
    • No built-in file upload/download API comparable to E2B's convenience features

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    🔒 Security & Compliance Comparison

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    Security FeatureE2BDaytona
    SOC2✅ Yes
    GDPR✅ Yes
    HIPAA
    SSO✅ Yes
    Self-Hosted❌ No✅ Yes
    On-Prem❌ No✅ Yes
    RBAC✅ Yes
    Audit Log✅ Yes
    Open Source✅ Yes✅ Yes
    API Key Auth✅ Yes
    Encryption at Rest✅ Yes
    Encryption in Transit✅ Yes
    Data ResidencyUS, EU
    Data RetentionConfigurable retention policies
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