Model Comparisons: Choose the Best Object Detection Model for Your Project
Choosing the right object detection model is crucial for the success of your computer vision project. Welcome to the Ultralytics Model Comparison Hub! This page centralizes detailed technical comparisons between state-of-the-art object detection models, focusing on the latest Ultralytics YOLO versions alongside other leading architectures like RTDETR, EfficientDet, and more.
Our goal is to equip you with the insights needed to select the optimal model based on your specific requirements, whether you prioritize maximum accuracy, real-time inference speed, computational efficiency, or a balance between them.
Get a quick overview of model performance with our interactive benchmark chart:
This chart visualizes key performance metrics like mAP (mean Average Precision) against inference latency, helping you quickly assess the trade-offs between different models often benchmarked on standard datasets like COCO.
Dive deeper with our specific comparison pages. Each analysis covers:
- Architectural Differences: Understand the core design principles, like the backbone and detection heads, and innovations.
- Performance Benchmarks: Compare metrics like accuracy (mAP), speed (FPS, latency), and parameter count using tools like the Ultralytics Benchmark mode.
- Strengths and Weaknesses: Identify where each model excels and its limitations based on evaluation insights.
- Ideal Use Cases: Determine which scenarios each model is best suited for, from edge AI devices to cloud platforms. Explore various Ultralytics Solutions for inspiration.
This detailed breakdown helps you weigh the pros and cons to find the model that perfectly matches your project's needs, whether for deployment on edge devices, cloud deployment, or research using frameworks like PyTorch.
Watch: YOLO Models Comparison: Ultralytics YOLO11 vs. YOLOv10 vs. YOLOv9 vs. Ultralytics YOLOv8 🎉
Navigate directly to the comparison you need using the lists below. We've organized them by model for easy access:
YOLO11 vs
- YOLO11 vs YOLOv10
- YOLO11 vs YOLOv9
- YOLO11 vs YOLOv8
- YOLO11 vs YOLOv7
- YOLO11 vs YOLOv6-3.0
- YOLO11 vs YOLOv5
- YOLO11 vs PP-YOLOE+
- YOLO11 vs DAMO-YOLO
- YOLO11 vs YOLOX
- YOLO11 vs RT-DETR
- YOLO11 vs EfficientDet
YOLOv10 vs
- YOLOv10 vs YOLO11
- YOLOv10 vs YOLOv9
- YOLOv10 vs YOLOv8
- YOLOv10 vs YOLOv7
- YOLOv10 vs YOLOv6-3.0
- YOLOv10 vs YOLOv5
- YOLOv10 vs PP-YOLOE+
- YOLOv10 vs DAMO-YOLO
- YOLOv10 vs YOLOX
- YOLOv10 vs RT-DETR
- YOLOv10 vs EfficientDet
YOLOv9 vs
- YOLOv9 vs YOLO11
- YOLOv9 vs YOLOv10
- YOLOv9 vs YOLOv8
- YOLOv9 vs YOLOv7
- YOLOv9 vs YOLOv6-3.0
- YOLOv9 vs YOLOv5
- YOLOv9 vs PP-YOLOE+
- YOLOv9 vs DAMO-YOLO
- YOLOv9 vs YOLOX
- YOLOv9 vs RT-DETR
- YOLOv9 vs EfficientDet
YOLOv8 vs
- YOLOv8 vs YOLO11
- YOLOv8 vs YOLOv10
- YOLOv8 vs YOLOv9
- YOLOv8 vs YOLOv7
- YOLOv8 vs YOLOv6-3.0
- YOLOv8 vs YOLOv5
- YOLOv8 vs PP-YOLOE+
- YOLOv8 vs DAMO-YOLO
- YOLOv8 vs YOLOX
- YOLOv8 vs RT-DETR
- YOLOv8 vs EfficientDet
YOLOv7 vs
- YOLOv7 vs YOLO11
- YOLOv7 vs YOLOv10
- YOLOv7 vs YOLOv9
- YOLOv7 vs YOLOv8
- YOLOv7 vs YOLOv6-3.0
- YOLOv7 vs YOLOv5
- YOLOv7 vs PP-YOLOE+
- YOLOv7 vs DAMO-YOLO
- YOLOv7 vs YOLOX
- YOLOv7 vs RT-DETR
- YOLOv7 vs EfficientDet
YOLOv6 vs
- YOLOv6-3.0 vs YOLO11
- YOLOv6-3.0 vs YOLOv10
- YOLOv6-3.0 vs YOLOv9
- YOLOv6-3.0 vs YOLOv8
- YOLOv6-3.0 vs YOLOv7
- YOLOv6-3.0 vs YOLOv5
- YOLOv6-3.0 vs PP-YOLOE+
- YOLOv6-3.0 vs DAMO-YOLO
- YOLOv6-3.0 vs YOLOX
- YOLOv6-3.0 vs RT-DETR
- YOLOv6-3.0 vs EfficientDet
YOLOv5 vs
- YOLOv5 vs YOLO11
- YOLOv5 vs YOLOv10
- YOLOv5 vs YOLOv9
- YOLOv5 vs YOLOv8
- YOLOv5 vs YOLOv7
- YOLOv5 vs YOLOv6-3.0
- YOLOv5 vs PP-YOLOE+
- YOLOv5 vs DAMO-YOLO
- YOLOv5 vs YOLOX
- YOLOv5 vs RT-DETR
- YOLOv5 vs EfficientDet
PP-YOLOE+ vs
- PP-YOLOE+ vs YOLO11
- PP-YOLOE+ vs YOLOv10
- PP-YOLOE+ vs YOLOv9
- PP-YOLOE+ vs YOLOv8
- PP-YOLOE+ vs YOLOv7
- PP-YOLOE+ vs YOLOv6-3.0
- PP-YOLOE+ vs YOLOv5
- PP-YOLOE+ vs DAMO-YOLO
- PP-YOLOE+ vs YOLOX
- PP-YOLOE+ vs RT-DETR
- PP-YOLOE+ vs EfficientDet
DAMO-YOLO vs
- DAMO-YOLO vs YOLO11
- DAMO-YOLO vs YOLOv10
- DAMO-YOLO vs YOLOv9
- DAMO-YOLO vs YOLOv8
- DAMO-YOLO vs YOLOv7
- DAMO-YOLO vs YOLOv6-3.0
- DAMO-YOLO vs YOLOv5
- DAMO-YOLO vs PP-YOLOE+
- DAMO-YOLO vs YOLOX
- DAMO-YOLO vs RT-DETR
- DAMO-YOLO vs EfficientDet
YOLOX vs
- YOLOX vs YOLO11
- YOLOX vs YOLOv10
- YOLOX vs YOLOv9
- YOLOX vs YOLOv8
- YOLOX vs YOLOv7
- YOLOX vs YOLOv6-3.0
- YOLOX vs YOLOv5
- YOLOX vs PP-YOLOE+
- YOLOX vs DAMO-YOLO
- YOLOX vs RT-DETR
- YOLOX vs EfficientDet
RT-DETR vs
- RT-DETR vs YOLO11
- RT-DETR vs YOLOv10
- RT-DETR vs YOLOv9
- RT-DETR vs YOLOv8
- RT-DETR vs YOLOv7
- RT-DETR vs YOLOv6-3.0
- RT-DETR vs YOLOv5
- RT-DETR vs PP-YOLOE+
- RT-DETR vs DAMO-YOLO
- RT-DETR vs YOLOX
- RT-DETR vs EfficientDet
EfficientDet vs
- EfficientDet vs YOLO11
- EfficientDet vs YOLOv10
- EfficientDet vs YOLOv9
- EfficientDet vs YOLOv8
- EfficientDet vs YOLOv7
- EfficientDet vs YOLOv6-3.0
- EfficientDet vs YOLOv5
- EfficientDet vs PP-YOLOE+
- EfficientDet vs DAMO-YOLO
- EfficientDet vs YOLOX
- EfficientDet vs RT-DETR
This index is continuously updated as new models are released and comparisons are made available. We encourage you to explore these resources to gain a deeper understanding of each model's capabilities and find the perfect fit for your next computer vision project. Happy comparing!
