Verne Robotics Open-Sources V0.5 World Action Model with Stronger Robustness
Verne Robotics released V0.5, an open-weight world action model built on the Wan2.2 video generator and trained on over 1.7M demonstrations, predicting the next second of arm, gripper and mobile-base motion. It learns new industrial tasks from under two hours of demos and degrades far less than Physical Intelligence's π0.5 under clutter and lighting shifts.
Full Report
Rohan Paul (@rohanpaul_ai) · 2026-11-05 18
Brilliant release by @VerneRobotics
V0.5, an open-weight world action model, that looks through cameras and outputs the next second of arm, gripper and mobile-base motion.
The big deal is that it learned new industrial tasks from under 2 hours of demonstrations.
Robot models usually stumble when a room changes. With clutter and new lighting that neither model trained on, Verne Robotics’ V0.5 lost 7.6 points in simulation, while Physical Intelligence’s π0.5 lost 24.7.
On RoboTwin 2.0, randomized clutter, lighting and textures cut V0.5 from 81.0% to 73.4% in Verne’s tests, while Physical Intelligence’s π0.5 fell from 70.7% to 46.0%.
Built on the Wan2.2 video generator, V0.5 learned from over 1.7M demonstrations to predict upcoming camera frames alongside the motion producing them.
↳ 引用 @VerneRobotics (Verne): Introducing V0.5, Verne’s open-weight world action model for industrial robots.
We believe democratizing robotics starts with making frontier foundation models open to everyone.
Bringing robots to every industry will take many teams, building on shared progress across many workflows.
V0.5 is the leading US-made open-weight model on LIBERO and RoboTwin 2.0 benchmarks.
We hope you’ll join us in putting V0.5 to work.
