YOLO26 is an end-to-end object detection and multi-task model family supporting detection, instance segmentation , pose estimation, oriented object detection, and image classification across five size variants from Nano to Extra Large. Released in January 2026, it removes Non-Maximum Suppression for lower latency and drops the Distribution Focal Loss module for better compatibility with edge and low-power hardware. This post covers the architecture, COCO benchmark results, download links, and comparisons to models including RF-DETR , LW-DETR, and D-FINE. YOLO models are a family of real-time computer vision models designed to handle a wide range of tasks, including object detection , segmentation , pose estimation , classification , and oriented object detection . Leveraging popular architectures, these models offer exceptional speed and accuracy, making them well-suited for applications across edge devices, cloud APIs, and more.…