LibreAI / AI Agents / OSWorld
// agents · xlang-ai/OSWorld

OSWorld

OSWorld — benchmark multimodal agents on open-ended tasks in real computer environments.

★ 3.2k stars⑂ 540 forksApache-2.0updated 2026-09
▦ visual — this project's README ships no embeddable screenshot,
so here's a placeholder. The guide below is complete regardless.
// project facts

Project facts

OSWorld is an open-source ai agents project by xlang-ai (xlang-ai/OSWorld on GitHub). It has 3,184 GitHub stars and 540 forks, is released under the Apache-2.0 license, and was last updated on GitHub on 14 September 2026.

GitHub stars
3,184
Forks
540
License
Apache-2.0
Last updated on GitHub
14 September 2026
Category
AI Agents
Listing
Full install guide
Official site
Official site
// how it works

How it works

  1. Clarify your goal

    Decide the first concrete outcome you want from it, so you can pick the right example, template or mode instead of exploring everything at once.

  2. Get the project

    Clone the repository (or install the published package) and skim its README quick start for the requirements for your platform.

  3. Install and configure

    Run the documented install step and set any required configuration — such as provider keys, data sources or local services — before the first run.

  4. Run your first task

    Execute the smallest documented example end to end, confirm the output is what you expected, then adapt it to your real data or workflow.

// features

Why people love it

Real computer environments

Agents act in genuine OS desktops, not simulations or screenshots-only sandboxes.

Multiple providers

Run on VMware/VirtualBox locally, Docker with KVM on servers, or Modal, Daytona and AWS sandboxes.

Agent baselines

Reference agents to compare your computer-use agent against.

Local and public evaluation

Run the official evaluation locally or via the public evaluation path, with per-domain scores.

Manual task examination

Inspect and run individual tasks by hand to debug agent behaviour.

Extensible task suite

A large suite of open-ended tasks across desktop applications and workflows.

Advertisement
// run it

Run it yourself

  1. Clone the repository

    Get the source so you can inspect, configure and run it locally.

    git clone https://github.com/xlang-ai/OSWorld.git
    cd OSWorld
  2. Install OSWorld

    Clone, optionally create the conda environment, and install requirements.

    git clone https://github.com/xlang-ai/OSWorld
    cd OSWorld
    pip install -r requirements.txt  # or: pip install desktop-env
  3. Run a quick start evaluation

    Launch an experiment with default settings, customising provider and VM path as needed.

    python quickstart.py  # see README Quick Start for provider options, e.g. --provider_name modal --headless true
// use cases

What you can build

Advertisement
// faq

Questions, answered

Who maintains OSWorld?

It is maintained by xlang-ai on GitHub (xlang-ai/OSWorld), where the source, issues and releases live.

Is it free to use?

Yes — it is free and open source under Apache-2.0, which permits use, modification and commercial redistribution, with licence/notice retention.

Does it need a paid API key?

OSWorld itself is free research code; evaluating an agent needs that agent's model/API access, and VM or cloud sandboxes may incur provider costs.

How does it compare to productivity computer-use products such as desktop agent apps?

Compared with productivity computer-use products such as desktop agent apps, OSWorld's distinguishing focus is: oSWorld — benchmark multimodal agents on open-ended tasks in real computer environments. Pick it when that focus matches your need; the alternative may suit you better if its broader or different scope is the priority.

How do I get started?

Clone https://github.com/xlang-ai/OSWorld (or install its published package), follow the README quick start to install and configure it, then run the smallest documented example — the Run section on this page mirrors those steps.

// keep exploring

Similar tools

AI Agents

OSWorld-V2

Benchmark computer-use agents on long, real-world desktop tasks.

★ 353 starsApache-2.0
View guide →
AI Agents

ClawBench

An open benchmark for browser AI agents on everyday tasks.

★ 975 starsApache-2.0
View guide →
AI Agents

WorkArena

WorkArena: ServiceNow's benchmark for how well web agents handle everyday knowledge-work tasks.

★ 275 starsNOASSERTION
View guide →
AI Agents

Tutti

Tutti — a real-time shared workspace where people and multiple AI agents build in tune, sharing context, files, apps and tasks

★ 3.8k starsApache-2.0
View guide →
AI Agents

UI-TARS-desktop

ByteDance's open-source multimodal AI agent stack: GUI agents that see and operate real desktops

★ 39.2k starsApache-2.0
View guide →
AI Agents

SWE-bench_Pro-os

A benchmark testing whether agents can solve long-horizon coding tasks.

★ 539 starsMIT
View guide →
// alternatives

Alternatives in AI Agents

The most-starred other AI Agents projects in the LibreAI catalogue — the realistic shortlist if OSWorld is not the right fit.

Get OSWorld

Free and open — grab the source, star the repo, and start creating.