KI-Agenten
OSWorld
OSWorld — benchmark multimodal agents on open-ended tasks in real computer environments.
★ 3,2 Tsd. SterneApache-2.0
Anleitung ansehen →OSWorld-V2 ist ein Open-Source-Projekt aus der Kategorie KI-Agenten von xlang-ai (xlang-ai/OSWorld-V2 auf GitHub). Es hat 353 Sterne auf GitHub und 53 Forks, wird unter der Lizenz Apache-2.0 veröffentlicht und wurde zuletzt am 1. Oktober 2026 auf GitHub aktualisiert.
Benchmark computer-use agents on long, real-world desktop tasks.
Decide what you want the project to do before installing anything.
Grab the source and skim the README for setup requirements.
Install dependencies and add any API keys or settings it needs.
Launch it and follow the example workflow from the docs.
Actual desktops, not mocks.
Dozens of steps, like real work.
Clicks, typing, navigation.
The software people actually use.
Standardized tasks and scoring.
Purpose-built for CUAs.
Download the source and move into the project folder.
git clone https://github.com/xlang-ai/OSWorld-V2.git
cd OSWorld-V2Isolate dependencies, then install requirements.
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txtLaunch using the entry point shown in the README.
python -m osworld_v2 # check README for the exact commandIt is an open-source project at xlang-ai/OSWorld-V2 with 53 forks. Check the contributors tab and recent commits to judge how active maintenance is.
Yes — Apache 2.0 allows commercial use and modification. Keep the license and notice files, and note it includes a patent grant.
Tasks spanning dozens of steps across real applications — not single-turn Q&A.
Virtualized OS environments per the setup docs; it's heavier than a chat benchmark.
Clone the repo and follow the README quickstart — the docs at https://osworld-v2.xlang.ai walk through setup.
OSWorld — benchmark multimodal agents on open-ended tasks in real computer environments.
Reliable computer use for any agent: drive real apps through accessibility trees, not pixel guessing.
A benchmark testing whether agents can solve long-horizon coding tasks.
ESP32 iPhone Agent — let an AI model use a real iPhone with a $7 ESP32: AirPlay eyes, USB HID hands, no computer, no jailbreak
A benchmark for tool-agent-user interaction in real-world domains.
An open benchmark for browser AI agents on everyday tasks.
Die anderen Projekte der Kategorie KI-Agenten mit den meisten Sternen im LibreAI-Katalog — die realistische Auswahl, falls OSWorld-V2 nicht das Richtige ist.
A personal AI that really does things — on any OS, with your data staying yours.
An agentic skills framework & software development methodology that works.
Agent harness optimization system with skills, memory and security for Claude Code, Codex and more
The agent that grows with you — a Python framework for adaptive AI agents.
DeepSeek's plugin-based agent harness where everything is a plugin.
Verwandte Projekte der Kategorie KI-Agenten im Katalog, die OSWorld-V2 bei den Sternen am nächsten stehen — zum Weiterstöbern auf beiden Seiten.
Agentic memory for LLM agents, from a published research project.
WorkArena: ServiceNow's benchmark for how well web agents handle everyday knowledge-work tasks.
Safety testing for agents, right in pytest.
A complete evaluation toolkit for AI agents.
The tougher, more robust successor to the MMLU benchmark.
An MCP-native AI coding agent and runtime in a single binary.
Kostenlos und offen — hol dir den Quellcode, gib dem Repository einen Stern und leg los.