Ant Group's LingBot-Vision: a 1B-param vision model matches DINOv3 on spatial and boundary perception

蚂蚁灵波LingBot-Vision实测：1B参数越级打平DINOv3

Ant Group's LingBot-Vision packs only 1B parameters yet matches or beats the 7B DINOv3 on spatial geometry and boundary perception. It handles fine-tuning-free video object tracking—draw a stroke to lock on—and hardware-level depth completion that catches transparent glass and reflective surfaces. Global image classification is just average. It targets embodied AI, robot navigation, and robotic arm grasping, and runs locally on an RTX 30-series GPU. The post doesn't disclose latency or power figures.

Why it matters: Ant Group's 1B LingBot-Vision matches DINOv3 on spatial geometry and boundary perception, with direct practical value for robot navigation and grasping, plus local deployment on consumer GPUs. Points off for missing latency and power data, and weak global classification limits...