• YOLOv3

Model	APval	APtest	AP50	SpeedGPU	FPSGPU		params	FLOPS
YOLOv3	43.3	43.3	63	4.8ms	208		61.9M	156.4B
YOLOv3-SPP	44.3	44.3	64.6	4.9ms	204		63.0M	157.0B
YOLOv3-tiny	17.6	34.9	34.9	1.7ms	588		8.9M	13.3B

• YOLOv5

Model	size (pixels)	mAPval 50-95	mAPval 50	Speed CPU b1 (ms)	Speed V100 b1 (ms)	Speed V100 b32 (ms)	params (M)	FLOPs @640 (B)
YOLOv5n	640	28	45.7	45	6.3	0.6	1.9	4.5
YOLOv5s	640	37.4	56.8	98	6.4	0.9	7.2	16.5
YOLOv5m	640	45.4	64.1	224	8.2	1.7	21.2	49
YOLOv5l	640	49	67.3	430	10.1	2.7	46.5	109.1
YOLOv5x	640	50.7	68.9	766	12.1	4.8	86.7	205.7
YOLOv5n6	1280	36	54.4	153	8.1	2.1	3.2	4.6
YOLOv5s6	1280	44.8	63.7	385	8.2	3.6	12.6	16.8
YOLOv5m6	1280	51.3	69.3	887	11.1	6.8	35.7	50
YOLOv5l6	1280	53.7	71.3	1784	15.8	10.5	76.8	111.4
YOLOv5x6 + TTA	1280 1536	55.0 55.8	72.7 72.7	3136 -	26.2 -	19.4 -	140.7 -	209.8 -

• YOLOv8

Model	size (pixels)	mAPval 50-95			Speed CPU ONNX (ms)	Speed A100 TensorRT (ms)	params (M)	FLOPs (B)
YOLOv8n	640	37.3			80.4	0.99	3.2	8.7
YOLOv8s	640	44.9			128.4	1.2	11.2	28.6
YOLOv8m	640	50.2			234.7	1.83	25.9	78.9
YOLOv8l	640	52.9			375.2	2.39	43.7	165.2
YOLOv8x	640	53.9			479.1	3.53	68.2	257.8

• YOLOv6

Model	Size	mAPval 0.5:0.95			SpeedT4 trt fp16 b1 (fps)	SpeedT4 trt fp16 b32 (fps)	Params (M)	FLOPs (G)
YOLOv6-N	640	37.5			779	1187	4.7	11.4
YOLOv6-S	640	45			339	484	18.5	45.3
YOLOv6-M	640	50			175	226	34.9	85.8
YOLOv6-L	640	52.8			98	116	59.6	150.7
YOLOv6-N6	1280	44.9			228	281	10.4	49.8
YOLOv6-S6	1280	50.3			98	108	41.4	198
YOLOv6-M6	1280	55.2			47	55	79.6	379.5
YOLOv6-L6	1280	57.2			26	29	140.4	673.4

• YOLOv7

Model	Test Size	APtest	AP50test	AP75test	batch 1 fps	batch 32 average time
YOLOv7	640	51.40%	69.70%	55.90%	161 fps	2.8 ms
YOLOv7-X	640	53.10%	71.20%	57.80%	114 fps	4.3 ms
YOLOv7-W6	1280	54.90%	72.60%	60.10%	84 fps	7.6 ms
YOLOv7-E6	1280	56.00%	73.50%	61.20%	56 fps	12.3 ms
YOLOv7-D6	1280	56.60%	74.00%	61.80%	44 fps	15.0 ms
YOLOv7-E6E	1280	56.80%	74.40%	62.10%	36 fps	18.7 ms

• YOLOv9

Model	Test Size	APval	AP50val	AP75val	Param.	FLOPs
YOLOv9-T	640	38.30%	53.10%	41.30%	2.0M	7.7G
YOLOv9-S	640	46.80%	63.40%	50.70%	7.1M	26.4G
YOLOv9-M	640	51.40%	68.10%	56.10%	20.0M	76.3G
YOLOv9-C	640	53.00%	70.20%	57.80%	25.3M	102.1G
YOLOv9-E	640	55.60%	72.80%	60.60%	57.3M	189.0G

• YOLOv10

Model	Test Size	APval			#Params	FLOPs	Latency
YOLOv10-N	640	38.50%			2.3M	6.7G	1.84ms
YOLOv10-S	640	46.30%			7.2M	21.6G	2.49ms
YOLOv10-M	640	51.10%			15.4M	59.1G	4.74ms
YOLOv10-B	640	52.50%			19.1M	92.0G	5.74ms
YOLOv10-L	640	53.20%			24.4M	120.3G	7.28ms
YOLOv10-X	640	54.40%			29.5M	160.4G	10.70ms

• PP-YOLO

Model	GPU number	images/GPU	backbone	input shape	Box APval	Box APtest	V100 FP32(FPS)	V100 TensorRT FP16(FPS)
PP-YOLO	8	24	ResNet50vd	608	44.8	45.2	72.9	155.6
PP-YOLO	8	24	ResNet50vd	512	43.9	44.4	89.9	188.4
PP-YOLO	8	24	ResNet50vd	416	42.1	42.5	109.1	215.4
PP-YOLO	8	24	ResNet50vd	320	38.9	39.3	132.2	242.2
PP-YOLO_2x	8	24	ResNet50vd	608	45.3	45.9	72.9	155.6
PP-YOLO_2x	8	24	ResNet50vd	512	44.4	45	89.9	188.4
PP-YOLO_2x	8	24	ResNet50vd	416	42.7	43.2	109.1	215.4
PP-YOLO_2x	8	24	ResNet50vd	320	39.5	40.1	132.2	242.2
PP-YOLO	4	32	ResNet18vd	512	29.2	29.5	357.1	657.9
PP-YOLO	4	32	ResNet18vd	416	28.6	28.9	409.8	719.4
PP-YOLO	4	32	ResNet18vd	320	26.2	26.4	480.7	763.4
PP-YOLOv2	8	12	ResNet50vd	640	49.1	49.5	68.9	106.5
PP-YOLOv2	8	12	ResNet101vd	640	49.7	50.3	49.5	87

• PP-YOLOE

Model	Epoch	GPU number	images/GPU	backbone	input shape	Box APval 0.5:0.95	Box APtest 0.5:0.95	Params(M)	FLOPs(G)	V100 FP32(FPS)	V100 TensorRT FP16(FPS)
PP-YOLOE+_s	80	8	8	cspresnet-s	640	43.7	43.9	7.93	17.36	208.3	333.3
PP-YOLOE+_m	80	8	8	cspresnet-m	640	49.8	50	23.43	49.91	123.4	208.3
PP-YOLOE+_l	80	8	8	cspresnet-l	640	52.9	53.3	52.2	110.07	78.1	149.2
PP-YOLOE+_x	80	8	8	cspresnet-x	640	54.7	54.9	98.42	206.59	45	95.2