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tizkovatereza/awesome-ai-sandboxes

Analysis updated 2026-05-18

55Audience · developerComplexity · 1/5Setup · easy

TLDR

A curated awesome-list comparing cloud sandbox providers built for AI agents, covering isolation method, GPU support, and pricing for roughly twenty providers.

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What do people build with it?

USE CASE 1

Compare sandbox providers by isolation method, such as microVMs, Docker, or full virtual machines.

USE CASE 2

Check which sandbox providers support GPU workloads or long-running sessions.

USE CASE 3

Look up official SDK languages and pricing before picking a provider for an AI agent project.

USE CASE 4

Check a linked leaderboard comparing sandbox startup times across providers.

How does it compare?

tizkovatereza/awesome-ai-sandboxesarman-bd/chromiumfishbhartiyashesh/purelymailcalendar
Stars555555
LanguageRustPython
Setup difficultyeasyeasymoderate
Complexity1/53/54/5
Audiencedeveloperdevelopergeneral

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 5min
No license is stated in the provided text.

In plain English

Awesome AI Sandboxes is a curated reference list of cloud sandbox providers built for AI agents. A sandbox, in this context, is an isolated computing environment where an AI agent can run code, install software, browse the web, or interact with a file system without affecting the host machine or other users. This list focuses specifically on providers designed to support AI-driven automation rather than general developer environments. The README is organized into sections: open-source providers, closed-source commercial providers, and a section for providers focused on browser or computer-use scenarios (where an AI controls a graphical desktop). Each entry includes details sourced from the provider's own documentation, covering how the sandbox is isolated (microVMs, Docker, full VMs), whether it supports GPU workloads, whether long-running sessions are possible, which programming languages have official SDKs, and pricing model. The project explicitly states that all claims link back to official sources, and that pull requests adding new entries must also cite official documentation. Providers listed include both well-known names in the AI infrastructure space and newer entrants. Isolation methods vary across entries: some use Firecracker microVMs (lightweight virtual machines designed for serverless workloads), some use Docker containers, and some provide full Linux virtual machines. Startup time, session duration limits, and whether a provider supports "bring your own compute" arrangements are noted where documented. The repository also links to several sandbox benchmarks, including a live leaderboard measuring startup times across providers and a SQLite insert performance test comparing file system I/O across five providers. The list covers roughly twenty providers in the truncated portion of the README. Contributions are welcomed under the condition that new entries cite official sources only. No software is included in the repository itself, it is purely a documentation and reference resource.

Copy-paste prompts

Prompt 1
What is the difference between a Firecracker microVM and a Docker container as used by AI agent sandboxes?
Prompt 2
Which sandbox providers in this list support GPU workloads for AI agents?
Prompt 3
Explain what 'bring your own compute' means for a sandbox provider.
Prompt 4
How do I contribute a new sandbox provider entry to this list?

Frequently asked questions

What is awesome-ai-sandboxes?

A curated awesome-list comparing cloud sandbox providers built for AI agents, covering isolation method, GPU support, and pricing for roughly twenty providers.

What license does awesome-ai-sandboxes use?

No license is stated in the provided text.

How hard is awesome-ai-sandboxes to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is awesome-ai-sandboxes for?

Mainly developer.

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