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YOLOv8 vs. RT-DETR vs. YOLOv7: The 2025 Detector Showdown
Discover which model excels in accuracy-per-watt and latency-per-frame for your next project.
5 min readSep 8, 2025
In the rapidly evolving world of computer vision, object detection models serve as the backbone for countless AI applications, from autonomous driving to industrial inspection. As ML engineers and AI enthusiasts, we’re constantly searching for the perfect balance between accuracy and efficiency. In this article, I’ll compare three leading object detection architectures — YOLOv8, RT-DETR, and YOLOv7 — to help you make informed decisions for your next project.
The State of Object Detection in 2025
Modern object detection has evolved significantly since the original YOLO (You Only Look Once) paper in 2015. Today’s models represent different philosophical approaches to the speed-accuracy tradeoff:
- YOLOv8: Ultralytics’ latest iteration focuses on improved accuracy while maintaining real-time performance.
- RT-DETR: A transformer-based detector that promises “DETRs Beat YOLOs” with end-to-end processing.
- YOLOv7: A highly optimized model that pushed the boundaries of efficiency on resource-constrained devices.
