## WebGym: A New Environment for Training Visual Web Agents WebGym has been introduced, an open-source environment designed for training realistic visual web agents. This tool stands out for its vast range of tasks, nearly 300,000, covering real-world websites and diverse difficulty levels. ## Scalability and Performance To scale reinforcement learning (RL), WebGym introduces a high-throughput asynchronous rollout system, optimized for web agents. This system speeds up trajectory sampling by 4-5x compared to standard implementations. Training a vision-language model, Qwen-3-VL-8B-Instruct, on WebGym led to an increase in the success rate on an out-of-distribution test set from 26.2% to 42.9%, surpassing agents based on proprietary models such as GPT-4o and GPT-5-Thinking. ## Implications WebGym's ability to improve performance on websites never seen during training represents a significant step forward in the development of robust and adaptable visual web agents. This is particularly important because many previous works focused on tasks on websites already seen during training.