OSWorld

One-Minute Overview#

OSWorld is a benchmarking platform specifically designed to evaluate multimodal AI agents' capabilities in performing complex tasks within real computer environments. Whether you're a researcher or developer, OSWorld helps you assess agent performance on operating system-level tasks such as file operations, web browsing, software installation, and other real-world scenarios. Its main advantage is providing near-realistic testing conditions, making evaluation results more reliable and trustworthy.

Core Value: Provides realistic evaluation of agent capabilities in computer environments, helping researchers and developers optimize multimodal AI systems

Quick Start#

Installation Difficulty: Medium - Requires setting up virtual machine environments and configuring dependencies

# Clone the OSWorld repository
git clone https://github.com/xlang-ai/OSWorld
# Change directory into the cloned repository
cd OSWorld
# Install required dependencies
pip install -r requirements.txt

Is this suitable for my scenario?

• ✅ AI Research: Evaluating multimodal agents' task execution capabilities at the OS level
• ✅ AI Development: Testing and optimizing agent performance in realistic environments
• ❌ Simple Task Testing: If you only need to test basic text understanding capabilities, this tool is overly complex
• ❌ No Virtual Machine Environment: Deployment will be challenging without suitable virtualization platform support

Core Capabilities#

1. Multi-Platform Support - Adapting to Different Deployment Environments#

• Supports multiple virtualization platforms including VMware, VirtualBox, Docker, and AWS
• Users can choose the most suitable deployment option based on their existing infrastructure Actual Value: No need to change existing IT environments to integrate the testing system, lowering deployment barriers

2. Rich Task Sets - Comprehensive Agent Capability Testing#

• Includes diverse real-world scenarios like file operations, web browsing, software installation
• Provides complex scenarios like Google account tasks requiring OAuth2.0 configuration Actual Value: Comprehensive evaluation of agents' adaptability and problem-solving abilities in varied realistic environments

3. Parallel Evaluation - High-Efficiency Large-Scale Testing#

• Supports multi-environment parallel execution, enabling evaluation completion within 1 hour on AWS
• Offers single-threaded and multi-threaded execution options for different scale testing needs Actual Value: Significantly improves testing efficiency, accelerating model iteration and optimization processes

4. Detailed Result Recording - In-depth Analysis of Agent Performance#

• Automatically records screenshots, actions, and videos of the testing process
• Provides result viewing tools and detailed evaluation metrics Actual Value: Helps researchers deeply understand agents' decision-making processes and error points for targeted improvements

Technology Stack & Integration#

Development Language: Python Key Dependencies: Python 3.10+, VMware Workstation Pro/VirtualBox, Docker (optional) Integration Method: Library/API, providing complete Python interface for customized agents

Maintenance Status#

• Development Activity: Very active, with multiple updates per month
• Recent Updates: July 2025 release of OSWorld-Verified version, significantly improving evaluation efficiency and accuracy
• Community Response: Actively addresses community feedback, continuously fixing issues and adding new features

Commercial & Licensing#

License: Apache-2.0

• ✅ Commercial Use: Permitted
• ✅ Modification: Allowed
• ⚠️ Restrictions: Must include appropriate copyright and license notices