Ultralytics YOLO26: Unified Real-Time End-to-End Vision Models

Benchmark Model Rank Results
human-pose-keypoint-estimation-on-coco-val2017YOLO26x-pose#81AP: 71.6AP50: 91.6
human-pose-keypoint-estimation-on-coco-val2017YOLO26l-pose#88AP: 70.4AP50: 90.5
human-pose-keypoint-estimation-on-coco-val2017YOLO11x-pose#90AP: 69.5AP50: 91.1
human-pose-keypoint-estimation-on-coco-val2017YOLO26m-pose#93AP: 68.8AP50: 89.9
human-pose-keypoint-estimation-on-coco-val2017YOLO11l-pose#98AP: 66.1AP50: 89.9
real-time-object-detection-on-coco-val2017YOLO26x (Objects365 pre-training)#8box AP: 57.5FPS (batch 1, GPU in brackets): 85 (T4)
real-time-object-detection-on-coco-val2017YOLO26l (Objects365 pre-training)#21box AP: 55.0FPS (batch 1, GPU in brackets): 161 (T4)
real-time-object-detection-on-coco-val2017YOLO26m (Objects365 pre-training)#45box AP: 53.1FPS (batch 1, GPU in brackets): 213 (T4)
real-time-object-detection-on-coco-val2017YOLO26s (Objects365 pre-training)#92box AP: 48.6FPS (batch 1, GPU in brackets): 400 (T4)
real-time-object-detection-on-coco-val2017YOLO26n (Objects365 pre-training)#126box AP: 40.9FPS (batch 1, GPU in brackets): 588 (T4)