Vero: An Open RL Recipe for General Visual Reasoning

We introduce Vero, a family of fully open vision-language models (VLMs) designed for general visual reasoning across diverse domains such as charts, science, and spatial understanding. By scaling reinforcement learning (RL) data with the 600K-sample Vero-600K dataset and task-routed rewards, Vero achieves state-of-the-art performance on 30 challenging benchmarks, demonstrating that broad data coverage is the key driver of strong RL scaling. All data, code, and models are publicly released.