object-detection

NVIDIA released LocateAnything-3B, a 3-billion parameter vision-language model that predicts bounding boxes in parallel rather than token-by-token, achieving up to 2.5× higher throughput compared to autoregressive approaches. The model, trained on 12M images with 138M+ queries and 785M bounding boxes, supports object detection, GUI element grounding, and robotics perception.

Liquid AI has released LFM2.5-VL-450M, a refreshed 450M-parameter vision-language model built on an updated LFM2.5-350M backbone. The model features a 32,768-token context window, supports 9 languages, handles native 512×512 pixel images, and adds bounding box prediction and function calling capabilities. Performance improvements span both vision and language benchmarks compared to its predecessor.