YOLO26 vs RF-DETR: speed, accuracy and licensing

This comparison examines YOLO26 from Ultralytics and RF-DETR from Roboflow for object detection and instance segmentation. The presenter recommends YOLO26 for smaller devices and easier deployment, while favoring RF-DETR for small objects, complex scenes and more precise segmentation.

The benchmark discussion separates AP50 from the stricter AP50:95 metric. The presenter cites nano detection scores of 40.9 for YOLO26 and 48.4 for RF-DETR on COCO. Reported Nvidia T4 timings with TensorRT are 1.7 ms and 2.3 ms respectively. These figures describe the cited benchmark conditions, rather than expected speed on every device.

The practical examples compare medium models on still images. YOLO26 uses a 640-pixel input size, while RF-DETR medium uses 576 by 576. The presenter finds more chairs and a handbag in the RF-DETR detection result and prefers its segmentation boundaries. These are judgments about the examples shown.

The presenter also discusses licensing as a deployment consideration. YOLO26 has broader task support in this comparison, including pose estimation, classification, oriented boxes and built-in tracking. The recommendation weighs those capabilities and the surrounding software ecosystem alongside the image results.