Yuanli Lingji

On the RoboColiseum benchmark built by Zhiyuan Robotics with universities and the open-source community, Yuanli Lingji's embodied foundation model DM0.5 ranks first on all four sub-leaderboards: instruction following (0.8444), spatial understanding (0.6146), disturbance adaptation (0.7344), and general manipulation (0.6370). The company says DM0.5 is currently the only model topping all four boards; it attributes the result to a strong pretraining base plus standard supervised fine-tuning, without task-specific optimization.

The model's core latency dropped from 534 ms to 57.49 ms, and it has native 60-second memory. In logistics sorting it averages about 3 seconds per item with accuracy above 99%, according to the company. Separately, GeoVLA, a collaboration between Yuanli Lingji, Tsinghua University and Tianjin University, was nominated for the IROS 2026 Cognitive Robotics Best Paper Award.