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InfraDaytona

Daytona

Secure, elastic sandboxes for running AI-generated code.

Category
Infra
Pricing
FREEMIUM
Source
Open core
Hosting
Hybrid
Platforms
APICLI
Models
Model-agnostic
Verified
Jun 8, 2026

Infrastructure for executing AI-generated code in isolated sandboxes — each a full composable computer with a dedicated kernel, filesystem, network stack, and allocated CPU, RAM, and disk. Sandboxes start in under 90ms, snapshot for persistence, and are driven programmatically through SDKs (Python, TypeScript, Ruby, Go, Java), an API, and a CLI. AGPL-3.0 and available as a managed service, self-hosted stack, or hybrid where you bring your own compute.

Capabilities 2

What it actually does — grouped by capability family.

  • Sandboxed code execution (primary capability)
  • Browser automation (secondary capability)

Pros & cons

  • Sub-100ms sandbox start
  • Full isolated kernel + FS
  • SDKs in many languages
  • Open-source, self-host option
  • AGPL-3.0 may deter some
  • Infra to manage if self-hosted
  • Newer entrant

Tags

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    InfraFREEMIUMOpen core

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    Firecracker microVM hardware isolation
    No native GPU sandboxes (vs Modal)
    • sandbox
    • code-execution
    • agents
    • open-source
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    Define cloud workloads in Python, deploy with one command — GPU access on demand, fast cold starts, fair-share pricing. The default 'I need to fine-tune a model from a Jupyter cell' platform.

    Python-decorator infra, no YAML/Dockerfiles
    SDK lock-in; migrating means rewriting
    • gpu
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    • python
    • training
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    Browserbase

    Headless browser infrastructure for AI agents.

    Managed cloud fleet of headless browsers that let AI agents browse, authenticate, and act on the web at scale. Sessions ship with stealth proxies, automated CAPTCHA solving, and observability, driven via API or the open-source Stagehand framework. Usage-based billing on top of a monthly base plan.

    Managed fleet scales to many sessions
    Usage-based cost on a monthly base
    • browser-automation
    • agents
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    • web-scraping
  • View Beam details
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    On-demand serverless GPU compute for AI, from Python.

    A serverless cloud for deploying AI inference endpoints, agent sandboxes, task queues, and containerized GPU workloads with a few lines of Python. It handles fast cold starts, autoscaling, and Docker-in-Docker execution across multiple cloud backends, and supports bring-your-own-compute. The Developer tier is free with recurring monthly credit; paid tiers add team features and scale, billed pay-as-you-go by GPU usage.

    Define GPU workloads in pure Python
    Smaller ecosystem than hyperscalers
    • gpu
    • serverless
    • python
    • inference
    • +1