Smol2Operator: Post-Training GUI Agents for Computer Use

Back to Articles Smol2Operator: Post-Training GUI Agents for Computer Use Published September 23, 2025 Update on GitHub Upvote 136 +130 Amir Mahla A-Mahla Follow merve merve Follow Sergio Paniego sergiopaniego Follow Vaibhav Srivastav reach-vb Follow Lewis Tunstall lewtun Follow TL;DR: This work shows how a lightweight vision–language model can acquire GUI-grounded skills and evolve into an agentic GUI coder. We release all training recipes, data-processing tools, resulting model, demo and datasets to enable full reproducibility and foster further research 🫡. Find the collection here. This video demonstrates the model obtained through the recipe described below, executing a task end-to-end. Table of Contents Introduction 1. Data Transformation and Unified Action Space The Challenge of Inconsistent Action Spaces Our Unified Approach Example Data Transformation Custom Action Space Adaptation with Action Space Converter Key Features Usage Example Transformed and Released Datasets 2. Phase 1: From Zero to Perception Training Data Optimization Experiments Image Resolution and Coordinate System Analysis Key Findings Phase 1 Results 3. Phase 2: From Perception to Cognition Training Data Phase 2 Results 4. All you need is Open Source 5. Conclusion What's Next? 💡 Additional Resources: • Github repository: https://github.com/huggingface/smol2operator • Datasets: smolagents/aguvis-stage-1, smolagents/aguvis-stage-2 Introduction Graphical User Interface (GUI) automation is one of the ...