Object Detection Leaderboard

Understand the real-time computer vision landscape and pick the best model and hardware for your use case.

Benchmark data tables

Accuracy vs model size for 58 models across 12 families. Highest accuracy: deimv2-x at 61.3 mAP@50-95 (51.2 M params). Lightest is deimv2-atto at 0.5 M params (27.5 mAP).
Model	Family	mAP@50-95 (%)	Params (M)	GFLOPs
deimv2-x	deimv2	61.3	51.2	151.6
ec-x	ec	61.1	49.9	151.0
ec-l	ec	60.1	33.0	101.0
rtdetrv4-x	rtdetrv4	60.0	62.6	202.0
deim-x	deim	59.6	62.6	202.0
dfine-x	dfine	59.3	62.6	202.0
deimv2-l	deimv2	58.6	32.5	96.3
rfdetr-l	rfdetr	58.5	33.9	340.0
ec-m	ec	58.4	19.4	53.0
rtdetr-x	rtdetr	57.9	67.4	234.0
deim-l	deim	57.8	31.2	91.0
rtdetrv4-l	rtdetrv4	57.8	31.2	91.0
rfdetr-m	rfdetr	57.4	33.7	0.0
dfine-l	dfine	57.3	31.2	91.0
yolov9c	yolov9	57.1	25.5	51.8
rtdetrv2-r101	rtdetrv2	56.8	76.6	259.0
rtdetrv4-m	rtdetrv4	56.5	19.6	57.0
yolox-x	yolox	56.3	99.1	141.2
yolov9m	yolov9	56.1	20.1	38.7
deimv2-m	deimv2	56.0	18.4	52.2
rtdetr-l	rtdetr	55.8	32.9	110.0
rtdetrv2-r50	rtdetrv2	55.7	42.9	136.0
deim-m	deim	55.4	19.6	57.0
yolox-l	yolox	55.4	54.2	78.0
rfdetr-s	rfdetr	55.1	32.1	0.0
dfine-m	dfine	55.1	19.6	57.0
rtdetrv2-r50m	rtdetrv2	54.8	36.6	100.0
ec-s	ec	54.3	9.9	26.0
rtdetr-r101	rtdetr	53.9	76.6	259.0
rtdetrv2-r34	rtdetrv2	53.2	31.4	92.0
deimv2-s	deimv2	53.0	9.8	25.6
rtdetrv4-s	rtdetrv4	52.8	10.3	25.0
rtdetr-r50	rtdetr	52.7	42.9	136.0
deim-s	deim	52.1	10.3	25.0
yolox-m	yolox	51.7	25.3	37.0
rfdetr-n	rfdetr	51.4	30.5	0.0
yolonas-l	yolonas	51.2	67.0	116.6
rtdetr-r50m	rtdetr	50.8	36.6	0.0
rtdetrv2-r18	rtdetrv2	50.8	20.2	60.0
dfine-s	dfine	50.7	10.3	25.0
yolonas-m	yolonas	50.5	51.2	88.9
yolov9s	yolov9	50.5	7.2	13.5
rtdetr-r34	rtdetr	48.2	31.4	91.0
deim-n	deim	46.8	3.8	7.0
deimv2-n	deimv2	46.7	3.6	6.9
yolonas-s	yolonas	46.5	19.1	32.8
rtdetr-r18	rtdetr	45.6	20.2	60.0
yolox-s	yolox	44.3	9.0	13.5
picodet-l	picodet	44.1	3.3	8.9
dfine-n	dfine	42.8	3.8	7.0
deimv2-pico	deimv2	42.2	1.5	5.2
yolov9t	yolov9	41.8	2.0	4.0
picodet-m	picodet	37.9	2.1	2.5
yolox-tiny	yolox	35.5	5.1	7.7
deimv2-femto	deimv2	34.5	1.0	1.7
picodet-s	picodet	30.4	1.0	0.7
yolox-nano	yolox	28.8	0.9	1.3
deimv2-atto	deimv2	27.5	0.5	0.8

Accuracy vs latency on NVIDIA A100 · PyTorch FP32 for 13 models across 3 families. Highest accuracy: dfine-x at 59.3 mAP@50-95. Fastest is rtdetr-r34 at 36.0 ms (27.8 FPS).
Model	Family	mAP@50-95 (%)	Latency (ms)	FPS	Params (M)
dfine-x	dfine	59.3	64.7	15.4	62.6
dfine-l	dfine	57.3	58.3	17.1	31.2
dfine-m	dfine	55.1	46.1	21.7	19.6
rtdetr-r101	rtdetr	53.9	53.6	18.6	76.6
rtdetr-r50	rtdetr	52.7	44.1	22.7	42.9
yolonas-l	yolonas	51.2	60.4	16.6	67.0
rtdetr-r50m	rtdetr	50.8	39.8	25.1	36.6
dfine-s	dfine	50.7	41.7	24.0	10.3
yolonas-m	yolonas	50.5	58.9	17.0	51.2
rtdetr-r34	rtdetr	48.2	36.0	27.8	31.4
yolonas-s	yolonas	46.5	60.1	16.6	19.1
rtdetr-r18	rtdetr	45.6	36.5	27.4	20.2
dfine-n	dfine	42.8	39.1	25.6	3.8

Accuracy vs latency on NVIDIA Jetson Orin Nano Super 8GB · PyTorch FP32 for 55 models across 11 families. Highest accuracy: dfine-x at 61.4 mAP@50-95. Fastest is yolox-tiny at 49.2 ms (20.3 FPS).
Model	Family	mAP@50-95 (%)	Latency (ms)	FPS	Params (M)
dfine-x	dfine	61.4	350.0	2.9	62.6
deimv2-x	deimv2	61.3	370.1	2.7	51.2
ec-x	ec	61.1	349.5	2.9	49.9
ec-l	ec	60.1	296.0	3.4	33.0
rtdetrv4-x	rtdetrv4	60.0	351.8	2.8	62.6
dfine-l	dfine	60.0	211.7	4.7	31.2
deim-x	deim	59.6	349.8	2.9	62.6
deimv2-l	deimv2	58.6	303.8	3.3	32.5
rfdetr-l	rfdetr	58.5	248.5	4.0	33.9
ec-m	ec	58.4	200.8	5.0	19.4
rtdetr-x	rtdetr	57.9	338.1	3.0	67.4
deim-l	deim	57.8	209.3	4.8	31.2
dfine-m	dfine	57.8	143.3	7.0	19.6
rtdetrv4-l	rtdetrv4	57.8	210.8	4.7	31.2
rfdetr-m	rfdetr	57.4	174.5	5.7	33.7
yolov9c	yolov9	57.1	155.6	6.4	25.5
rtdetr-r101	rtdetr	56.8	359.6	2.8	76.6
rtdetrv2-r101	rtdetrv2	56.8	358.7	2.8	76.6
rtdetrv4-m	rtdetrv4	56.5	143.1	7.0	19.6
yolox-x	yolox	56.3	289.6	3.5	99.1
yolov9m	yolov9	56.1	124.8	8.0	20.1
deimv2-m	deimv2	56.0	213.5	4.7	18.4
rtdetr-r50	rtdetr	55.9	234.6	4.3	42.9
rtdetr-l	rtdetr	55.8	206.0	4.9	32.9
rtdetrv2-r50	rtdetrv2	55.7	233.4	4.3	42.9
deim-m	deim	55.4	143.7	7.0	19.6
yolox-l	yolox	55.4	171.7	5.8	54.2
rfdetr-s	rfdetr	55.1	144.6	6.9	32.1
rtdetrv2-r50m	rtdetrv2	54.8	196.8	5.1	36.6
ec-s	ec	54.3	168.2	6.0	9.9
rtdetr-r50m	rtdetr	53.8	198.3	5.0	36.6
dfine-s	dfine	53.4	96.8	10.3	10.3
rtdetrv2-r34	rtdetrv2	53.2	123.1	8.1	31.4
deimv2-s	deimv2	53.0	175.8	5.7	9.8
rtdetrv4-s	rtdetrv4	52.8	99.3	10.1	10.3
rtdetr-r34	rtdetr	52.2	125.8	8.0	31.4
deim-s	deim	52.1	98.1	10.2	10.3
yolox-m	yolox	51.7	110.1	9.1	25.3
rfdetr-n	rfdetr	51.4	98.3	10.2	30.5
rtdetrv2-r18	rtdetrv2	50.8	97.4	10.3	20.2
yolov9s	yolov9	50.5	101.2	9.9	7.2
rtdetr-r18	rtdetr	49.8	98.3	10.2	20.2
deim-n	deim	46.8	88.5	11.3	3.8
deimv2-n	deimv2	46.7	89.8	11.1	3.6
dfine-n	dfine	45.8	85.5	11.7	3.8
yolox-s	yolox	44.3	59.2	16.9	9.0
picodet-l	picodet	44.1	90.1	11.1	3.3
deimv2-pico	deimv2	42.2	71.1	14.1	1.5
yolov9t	yolov9	41.8	101.2	9.9	2.0
picodet-m	picodet	37.9	80.3	12.5	2.1
yolox-tiny	yolox	35.5	49.2	20.3	5.1
deimv2-femto	deimv2	34.5	67.5	14.8	1.0
picodet-s	picodet	30.4	72.2	13.8	1.0
yolox-nano	yolox	28.8	54.5	18.4	0.9
deimv2-atto	deimv2	27.5	64.9	15.4	0.5

Accuracy vs latency on NVIDIA Jetson Orin Nano Super 8GB · ONNX Runtime FP32 for 55 models across 11 families. Highest accuracy: dfine-x at 61.4 mAP@50-95. Fastest is deimv2-atto at 22.8 ms (43.9 FPS).
Model	Family	mAP@50-95 (%)	Latency (ms)	FPS	Params (M)
dfine-x	dfine	61.4	328.9	3.0	61.9
deimv2-x	deimv2	61.3	444.9	2.3	50.3
ec-x	ec	61.1	422.4	2.4	49.3
ec-l	ec	60.1	367.3	2.7	33.0
rtdetrv4-x	rtdetrv4	60.0	342.2	2.9	62.8
dfine-l	dfine	60.0	199.6	5.0	30.9
deim-x	deim	59.6	328.8	3.0	61.9
rfdetr-l	rfdetr	58.6	295.5	3.4	30.4
deimv2-l	deimv2	58.5	370.2	2.7	32.2
ec-m	ec	58.4	254.4	3.9	19.5
rtdetr-x	rtdetr	58.0	331.4	3.0	67.5
deim-l	deim	57.8	199.7	5.0	30.9
dfine-m	dfine	57.8	144.4	6.9	19.4
rtdetrv4-l	rtdetrv4	57.8	206.5	4.8	31.3
rfdetr-m	rfdetr	57.4	204.7	4.9	30.1
yolov9c	yolov9	57.1	156.1	6.4	25.5
rtdetr-r101	rtdetr	56.8	343.9	2.9	76.7
rtdetrv2-r101	rtdetrv2	56.8	343.3	2.9	76.7
rtdetrv4-m	rtdetrv4	56.5	149.1	6.7	19.6
yolox-x	yolox	56.3	273.8	3.6	99.0
yolov9m	yolov9	56.1	128.1	7.8	20.1
deimv2-m	deimv2	56.0	260.4	3.8	18.4
rtdetr-r50	rtdetr	55.9	228.0	4.4	43.0
rtdetr-l	rtdetr	55.8	206.5	4.8	33.0
rtdetrv2-r50	rtdetrv2	55.7	227.4	4.4	43.0
yolox-l	yolox	55.5	161.9	6.2	54.2
deim-m	deim	55.4	144.6	6.9	19.4
rfdetr-s	rfdetr	55.1	161.5	6.2	28.5
rtdetrv2-r50m	rtdetrv2	54.8	184.3	5.4	33.3
ec-s	ec	54.3	192.3	5.2	10.1
rtdetr-r50m	rtdetr	53.8	184.5	5.4	33.3
dfine-s	dfine	53.4	96.1	10.4	10.3
rtdetrv2-r34	rtdetrv2	53.2	131.5	7.6	31.5
deimv2-s	deimv2	53.0	194.4	5.1	10.0
rtdetrv4-s	rtdetrv4	52.8	97.5	10.3	10.4
rtdetr-r34	rtdetr	52.2	131.7	7.6	31.5
deim-s	deim	52.1	96.2	10.4	10.3
yolox-m	yolox	51.8	107.3	9.3	25.3
rfdetr-n	rfdetr	51.4	96.0	10.4	26.9
rtdetrv2-r18	rtdetrv2	50.8	103.5	9.7	20.3
yolov9s	yolov9	50.4	79.8	12.5	7.2
rtdetr-r18	rtdetr	49.8	103.7	9.6	20.3
deim-n	deim	46.8	57.2	17.5	3.8
deimv2-n	deimv2	46.7	56.8	17.6	3.6
dfine-n	dfine	45.8	57.0	17.5	3.8
yolox-s	yolox	44.3	58.6	17.1	9.0
picodet-l	picodet	43.6	232.1	4.3	3.3
deimv2-pico	deimv2	42.3	47.1	21.3	1.5
yolov9t	yolov9	41.8	53.8	18.6	2.0
picodet-m	picodet	37.3	93.4	10.7	2.1
yolox-tiny	yolox	35.5	31.8	31.4	5.0
deimv2-femto	deimv2	34.5	26.9	37.1	1.0
picodet-s	picodet	29.6	61.1	16.4	1.0
yolox-nano	yolox	28.8	29.1	34.4	0.9
deimv2-atto	deimv2	27.5	22.8	43.9	0.5

Accuracy vs latency on NVIDIA Jetson Orin Nano Super 8GB · TensorRT FP32 for 55 models across 11 families. Highest accuracy: dfine-x at 61.5 mAP@50-95. Fastest is deimv2-atto at 12.3 ms (81.4 FPS).
Model	Family	mAP@50-95 (%)	Latency (ms)	FPS	Params (M)
dfine-x	dfine	61.5	124.8	8.0	62.0
deimv2-x	deimv2	61.3	194.2	5.2	50.3
ec-x	ec	61.1	186.5	5.4	49.0
ec-l	ec	60.1	163.8	6.1	31.0
rtdetrv4-x	rtdetrv4	60.0	128.3	7.8	62.0
dfine-l	dfine	60.0	80.2	12.5	31.0
deim-x	deim	59.6	125.1	8.0	62.0
rfdetr-l	rfdetr	58.6	127.8	7.8	128.0
deimv2-l	deimv2	58.6	163.3	6.1	32.2
ec-m	ec	58.3	121.6	8.2	18.0
rtdetr-x	rtdetr	58.0	115.8	8.6	67.0
deim-l	deim	57.8	80.5	12.4	31.0
rtdetrv4-l	rtdetrv4	57.8	82.4	12.1	31.0
dfine-m	dfine	57.7	63.5	15.8	19.0
rfdetr-m	rfdetr	57.4	85.9	11.6	33.7
yolov9c	yolov9	57.1	76.0	13.2	25.5
rtdetr-r101	rtdetr	56.8	118.5	8.4	76.0
rtdetrv2-r101	rtdetrv2	56.8	118.2	8.5	76.0
rtdetrv4-m	rtdetrv4	56.4	65.0	15.4	19.0
yolox-x	yolox	56.3	149.3	6.7	99.1
yolov9m	yolov9	56.1	68.9	14.5	20.1
deimv2-m	deimv2	55.9	125.4	8.0	18.1
rtdetr-r50	rtdetr	55.9	79.1	12.6	42.0
rtdetr-l	rtdetr	55.8	73.5	13.6	32.0
rtdetrv2-r50	rtdetrv2	55.7	78.6	12.7	42.0
deim-m	deim	55.5	63.8	15.7	19.0
yolox-l	yolox	55.4	87.5	11.4	54.2
rfdetr-s	rfdetr	55.1	69.1	14.5	32.1
rtdetrv2-r50m	rtdetrv2	54.8	63.3	15.8	36.0
ec-s	ec	54.4	94.8	10.6	9.9
rtdetr-r50m	rtdetr	53.8	63.6	15.7	36.6
dfine-s	dfine	53.4	44.7	22.4	10.0
rtdetrv2-r34	rtdetrv2	53.2	58.0	17.3	31.0
deimv2-s	deimv2	53.0	95.7	10.4	9.7
rtdetrv4-s	rtdetrv4	52.9	45.3	22.1	10.0
rtdetr-r34	rtdetr	52.2	58.5	17.1	31.0
deim-s	deim	52.1	45.0	22.2	10.0
yolox-m	yolox	51.8	61.1	16.4	25.3
rfdetr-n	rfdetr	51.4	42.1	23.7	30.5
rtdetrv2-r18	rtdetrv2	50.7	44.8	22.3	20.0
yolov9s	yolov9	50.5	46.2	21.6	7.2
rtdetr-r18	rtdetr	49.8	45.3	22.1	20.0
deim-n	deim	46.8	30.0	33.4	4.0
deimv2-n	deimv2	46.7	30.3	33.0	3.6
dfine-n	dfine	45.8	29.9	33.5	4.0
yolox-s	yolox	44.3	38.3	26.1	9.0
picodet-l	picodet	44.1	60.8	16.4	3.3
deimv2-pico	deimv2	42.3	26.5	37.7	1.5
yolov9t	yolov9	41.8	36.0	27.8	2.0
picodet-m	picodet	37.9	33.7	29.6	2.1
yolox-tiny	yolox	35.5	23.0	43.6	5.1
deimv2-femto	deimv2	34.5	16.7	60.0	1.0
picodet-s	picodet	30.4	26.4	37.9	1.0
yolox-nano	yolox	28.8	21.1	47.4	0.9
deimv2-atto	deimv2	27.5	12.3	81.4	0.5

Accuracy vs latency on NVIDIA RTX 5070 Ti · ONNX Runtime FP32 for 55 models across 11 families. Highest accuracy: dfine-x at 61.4 mAP@50-95. Fastest is deimv2-atto at 9.8 ms (102.0 FPS).
Model	Family	mAP@50-95 (%)	Latency (ms)	FPS	Params (M)
dfine-x	dfine	61.4	24.1	41.5	61.7
deimv2-x	deimv2	61.4	36.9	27.1	50.3
ec-x	ec	61.1	31.3	31.9	49.0
ec-l	ec	60.1	29.8	33.6	32.7
rtdetrv4-x	rtdetrv4	60.0	26.1	38.3	62.6
dfine-l	dfine	60.0	19.6	50.9	30.8
deim-x	deim	59.6	25.1	39.8	61.7
rfdetr-l	rfdetr	58.6	22.8	43.8	30.3
deimv2-l	deimv2	58.6	31.9	31.4	32.2
ec-m	ec	58.4	24.9	40.2	19.2
rtdetr-x	rtdetr	58.0	20.7	48.4	67.3
deim-l	deim	57.8	19.8	50.5	30.8
rtdetrv4-l	rtdetrv4	57.8	20.8	48.0	31.2
dfine-m	dfine	57.8	16.7	59.8	19.3
rfdetr-m	rfdetr	57.4	16.7	59.8	30.1
yolov9c	yolov9	57.1	15.7	63.5	25.5
rtdetr-r101	rtdetr	56.8	21.1	47.5	76.5
rtdetrv2-r101	rtdetrv2	56.8	20.3	49.3	76.6
rtdetrv4-m	rtdetrv4	56.5	17.7	56.6	19.5
yolox-x	yolox	56.3	24.0	41.6	99.0
yolov9m	yolov9	56.1	15.5	64.5	20.1
deimv2-m	deimv2	56.0	27.7	36.0	18.1
rtdetr-r50	rtdetr	55.9	15.9	62.8	42.8
rtdetr-l	rtdetr	55.8	15.5	64.5	32.8
rtdetrv2-r50	rtdetrv2	55.6	15.2	66.0	42.9
deim-m	deim	55.5	17.4	57.6	19.3
yolox-l	yolox	55.4	19.8	50.6	54.2
rfdetr-s	rfdetr	55.1	14.6	68.5	28.5
rtdetrv2-r50m	rtdetrv2	54.8	12.6	79.6	33.2
ec-s	ec	54.3	23.4	42.8	9.8
rtdetr-r50m	rtdetr	53.8	13.1	76.4	33.1
dfine-s	dfine	53.4	14.1	70.9	10.3
rtdetrv2-r34	rtdetrv2	53.2	12.3	81.1	31.4
deimv2-s	deimv2	53.0	25.2	39.6	9.7
rtdetrv4-s	rtdetrv4	52.8	15.0	66.7	10.3
rtdetr-r34	rtdetr	52.2	12.9	77.7	31.3
deim-s	deim	52.1	14.8	67.5	10.3
yolox-m	yolox	51.8	17.9	55.8	25.3
rfdetr-n	rfdetr	51.4	15.2	65.7	26.9
rtdetrv2-r18	rtdetrv2	50.8	10.3	97.1	20.1
yolov9s	yolov9	50.4	18.3	54.5	7.2
rtdetr-r18	rtdetr	49.8	10.8	92.5	20.1
deim-n	deim	46.8	13.2	75.9	3.8
deimv2-n	deimv2	46.7	13.1	76.3	3.6
dfine-n	dfine	45.8	12.7	78.9	3.8
yolox-s	yolox	44.3	16.5	60.6	9.0
picodet-l	picodet	44.1	29.2	34.3	3.3
deimv2-pico	deimv2	42.3	12.5	80.2	1.5
yolov9t	yolov9	41.8	19.2	52.1	2.0
picodet-m	picodet	37.9	21.7	46.0	2.1
yolox-tiny	yolox	35.5	13.1	76.2	5.0
deimv2-femto	deimv2	34.5	11.1	90.3	1.0
picodet-s	picodet	30.4	17.9	55.8	1.0
yolox-nano	yolox	28.8	15.8	63.2	0.9
deimv2-atto	deimv2	27.5	9.8	102.0	0.5

Accuracy vs latency on NVIDIA RTX 5070 Ti · TensorRT FP16 for 51 models across 11 families. Highest accuracy: dfine-x at 61.5 mAP@50-95. Fastest is rtdetrv2-r34 at 7.5 ms (132.9 FPS).
Model	Family	mAP@50-95 (%)	Latency (ms)	FPS	Params (M)
dfine-x	dfine	61.5	13.7	73.0	62.0
ec-x	ec	61.0	24.2	41.3	49.0
deimv2-x	deimv2	60.8	26.4	37.9	50.3
dfine-l	dfine	60.0	14.4	69.3	31.0
ec-l	ec	60.0	24.0	41.7	31.0
rtdetrv4-x	rtdetrv4	60.0	14.1	71.0	62.0
deim-x	deim	59.5	14.1	70.7	62.0
rfdetr-l	rfdetr	58.6	21.0	47.6	128.0
deimv2-l	deimv2	58.5	25.9	38.7	32.2
ec-m	ec	58.2	20.5	48.9	18.0
rtdetr-x	rtdetr	57.9	12.2	82.3	67.0
rtdetrv4-l	rtdetrv4	57.7	12.8	78.0	31.0
dfine-m	dfine	57.6	13.4	74.5	19.0
rfdetr-m	rfdetr	57.4	15.9	62.9	33.7
yolov9c	yolov9	57.2	13.4	74.7	25.5
rtdetrv2-r101	rtdetrv2	56.8	11.4	87.4	76.0
rtdetr-r101	rtdetr	56.7	11.4	88.0	76.0
rtdetrv4-m	rtdetrv4	56.4	11.5	86.7	19.0
yolox-x	yolox	56.3	13.9	72.1	99.1
yolov9m	yolov9	56.1	13.8	72.3	20.1
rtdetr-l	rtdetr	55.8	8.2	122.0	32.0
rtdetr-r50	rtdetr	55.8	10.3	97.4	42.0
rtdetrv2-r50	rtdetrv2	55.7	9.7	103.6	42.0
yolox-l	yolox	55.4	12.6	79.3	54.2
deim-m	deim	55.4	12.0	83.3	19.0
rfdetr-s	rfdetr	55.3	14.0	71.6	32.1
rtdetrv2-r50m	rtdetrv2	54.7	8.9	113.0	36.0
ec-s	ec	54.4	23.0	43.5	9.9
rtdetr-r50m	rtdetr	53.9	9.1	110.1	36.6
dfine-s	dfine	53.2	11.6	86.5	10.0
rtdetrv2-r34	rtdetrv2	53.2	7.5	132.9	31.0
deimv2-s	deimv2	53.0	19.8	50.4	9.7
rtdetrv4-s	rtdetrv4	52.9	10.8	92.3	10.0
rtdetr-r34	rtdetr	52.3	9.2	108.4	31.0
deim-s	deim	51.9	12.1	82.4	10.0
yolox-m	yolox	51.6	12.0	83.0	25.3
rfdetr-n	rfdetr	51.4	17.1	58.3	30.5
rtdetrv2-r18	rtdetrv2	50.8	8.5	117.8	20.0
yolov9s	yolov9	50.5	15.7	63.8	7.2
rtdetr-r18	rtdetr	49.8	8.8	113.4	20.0
deimv2-n	deimv2	46.6	12.8	78.0	3.6
deim-n	deim	46.6	12.3	81.3	4.0
dfine-n	dfine	45.8	12.5	79.7	4.0
picodet-l	picodet	44.0	26.3	38.0	3.3
yolox-s	yolox	43.4	14.1	70.9	9.0
yolov9t	yolov9	41.8	17.0	59.0	2.0
picodet-m	picodet	37.3	15.2	65.7	2.1
yolox-tiny	yolox	35.4	10.2	97.7	5.1
picodet-s	picodet	30.4	12.7	78.6	1.0
yolox-nano	yolox	28.7	10.0	100.0	0.9
deimv2-atto	deimv2	25.8	7.6	132.1	0.5

Accuracy vs latency on NVIDIA RTX 5070 Ti · TensorRT FP32 for 55 models across 11 families. Highest accuracy: dfine-x at 61.4 mAP@50-95. Fastest is deimv2-atto at 7.3 ms (137.9 FPS).
Model	Family	mAP@50-95 (%)	Latency (ms)	FPS	Params (M)
dfine-x	dfine	61.4	17.3	57.9	62.0
deimv2-x	deimv2	61.3	26.2	38.1	50.3
ec-x	ec	61.1	21.9	45.6	49.0
ec-l	ec	60.1	20.4	49.0	31.0
rtdetrv4-x	rtdetrv4	60.0	17.1	58.3	62.0
dfine-l	dfine	60.0	13.8	72.3	31.0
deim-x	deim	59.6	17.1	58.6	62.0
deimv2-l	deimv2	58.6	23.2	43.2	32.2
rfdetr-l	rfdetr	58.6	22.2	45.1	128.0
ec-m	ec	58.4	16.9	59.2	18.0
rtdetr-x	rtdetr	57.9	14.6	68.5	67.0
deim-l	deim	57.9	13.2	75.7	31.0
rtdetrv4-l	rtdetrv4	57.8	13.8	72.7	31.0
dfine-m	dfine	57.8	11.7	85.3	19.0
rfdetr-m	rfdetr	57.4	15.7	63.7	33.7
yolov9c	yolov9	57.1	13.0	76.7	25.5
rtdetr-r101	rtdetr	56.8	15.5	64.4	76.0
rtdetrv2-r101	rtdetrv2	56.8	15.4	64.8	76.0
rtdetrv4-m	rtdetrv4	56.5	11.9	84.4	19.0
yolox-x	yolox	56.3	20.7	48.4	99.1
yolov9m	yolov9	56.1	12.9	77.5	20.1
deimv2-m	deimv2	56.0	20.2	49.6	18.1
rtdetr-r50	rtdetr	55.9	11.4	87.4	42.0
rtdetr-l	rtdetr	55.7	10.6	94.2	32.0
rtdetrv2-r50	rtdetrv2	55.7	11.3	88.5	42.0
deim-m	deim	55.5	11.7	85.4	19.0
yolox-l	yolox	55.4	16.2	61.8	54.2
rfdetr-s	rfdetr	55.1	12.9	77.5	32.1
rtdetrv2-r50m	rtdetrv2	54.8	9.7	103.3	36.0
ec-s	ec	54.4	15.8	63.4	9.9
rtdetr-r50m	rtdetr	53.9	9.7	102.8	36.6
dfine-s	dfine	53.4	10.1	98.7	10.0
rtdetrv2-r34	rtdetrv2	53.2	9.8	102.5	31.0
deimv2-s	deimv2	53.0	19.0	52.5	9.7
rtdetrv4-s	rtdetrv4	52.9	10.3	97.1	10.0
rtdetr-r34	rtdetr	52.2	10.2	98.1	31.0
deim-s	deim	52.1	10.2	97.6	10.0
yolox-m	yolox	51.7	14.3	70.1	25.3
rfdetr-n	rfdetr	51.4	14.8	67.6	30.5
rtdetrv2-r18	rtdetrv2	50.7	8.0	125.5	20.0
yolov9s	yolov9	50.5	13.3	75.1	7.2
rtdetr-r18	rtdetr	49.8	8.3	120.6	20.0
deim-n	deim	46.8	14.8	67.5	4.0
deimv2-n	deimv2	46.7	14.3	70.1	3.6
dfine-n	dfine	45.8	10.1	98.7	4.0
yolox-s	yolox	44.3	13.4	74.5	9.0
picodet-l	picodet	44.1	31.3	32.0	3.3
deimv2-pico	deimv2	42.2	12.5	79.9	1.5
yolov9t	yolov9	41.8	13.9	72.0	2.0
picodet-m	picodet	36.0	18.7	53.5	2.1
deimv2-femto	deimv2	34.3	8.4	119.0	1.0
yolox-tiny	yolox	33.9	11.5	87.2	5.1
picodet-s	picodet	30.3	13.5	74.0	1.0
yolox-nano	yolox	28.6	11.5	86.7	0.9
deimv2-atto	deimv2	27.5	7.3	137.9	0.5

Accuracy vs latency on NVIDIA Jetson Orin Nano Super 8GB · TensorRT FP16 for 55 models across 11 families. Highest accuracy: dfine-x at 61.4 mAP@50-95. Fastest is deimv2-atto at 11.2 ms (89.1 FPS).
Model	Family	mAP@50-95 (%)	Latency (ms)	FPS	Params (M)
dfine-x	dfine	61.4	70.5	14.2	62.0
ec-x	ec	61.0	174.8	5.7	49.0
deimv2-x	deimv2	60.8	184.5	5.4	50.3
ec-l	ec	60.0	161.5	6.2	31.0
dfine-l	dfine	60.0	53.6	18.6	31.0
rtdetrv4-x	rtdetrv4	60.0	72.7	13.8	62.0
deim-x	deim	59.6	70.9	14.1	62.0
rfdetr-l	rfdetr	58.7	119.3	8.4	128.0
deimv2-l	deimv2	58.5	160.8	6.2	32.2
ec-m	ec	58.3	119.7	8.3	18.0
dfine-m	dfine	57.9	42.3	23.7	19.0
deim-l	deim	57.9	54.0	18.5	31.0
rtdetr-x	rtdetr	57.9	58.9	17.0	67.0
rtdetrv4-l	rtdetrv4	57.8	55.2	18.1	31.0
rfdetr-m	rfdetr	57.4	79.8	12.5	33.7
yolov9c	yolov9	57.1	40.1	24.9	25.5
rtdetr-r101	rtdetr	56.8	58.8	17.0	76.0
rtdetrv2-r101	rtdetrv2	56.8	57.7	17.3	76.0
rtdetrv4-m	rtdetrv4	56.5	43.3	23.1	19.0
yolox-x	yolox	56.2	68.7	14.6	99.1
yolov9m	yolov9	56.1	38.8	25.8	20.1
deimv2-m	deimv2	56.0	126.5	7.9	18.1
rtdetr-l	rtdetr	55.8	41.5	24.1	32.0
rtdetr-r50	rtdetr	55.7	42.4	23.6	42.0
rtdetrv2-r50	rtdetrv2	55.7	41.3	24.2	42.0
deim-m	deim	55.5	42.5	23.5	19.0
yolox-l	yolox	55.5	46.3	21.6	54.2
rfdetr-s	rfdetr	55.2	64.4	15.5	32.1
rtdetrv2-r50m	rtdetrv2	54.8	33.6	29.7	36.0
ec-s	ec	54.3	94.8	10.6	9.9
rtdetr-r50m	rtdetr	53.8	34.3	29.1	36.6
dfine-s	dfine	53.5	33.1	30.2	10.0
rtdetrv2-r34	rtdetrv2	53.2	30.6	32.7	31.0
deimv2-s	deimv2	53.0	95.5	10.5	9.7
rtdetrv4-s	rtdetrv4	52.9	33.7	29.6	10.0
rtdetr-r34	rtdetr	52.3	31.4	31.9	31.0
deim-s	deim	52.0	33.4	29.9	10.0
yolox-m	yolox	51.8	35.7	28.0	25.3
rfdetr-n	rfdetr	51.3	39.4	25.4	30.5
rtdetrv2-r18	rtdetrv2	50.8	25.1	39.9	20.0
yolov9s	yolov9	50.4	30.1	33.2	7.2
rtdetr-r18	rtdetr	49.7	25.7	38.8	20.0
deim-n	deim	46.8	23.9	41.8	4.0
deimv2-n	deimv2	46.6	24.3	41.2	3.6
dfine-n	dfine	45.8	23.8	42.1	4.0
yolox-s	yolox	44.2	28.6	34.9	9.0
picodet-l	picodet	44.0	52.3	19.1	3.3
deimv2-pico	deimv2	42.3	22.5	44.5	1.5
yolov9t	yolov9	41.8	29.1	34.3	2.0
picodet-m	picodet	37.9	30.8	32.4	2.1
yolox-tiny	yolox	35.5	19.4	51.6	5.1
deimv2-femto	deimv2	34.5	15.2	65.7	1.0
picodet-s	picodet	30.4	25.3	39.6	1.0
yolox-nano	yolox	28.8	19.6	51.0	0.9
deimv2-atto	deimv2	27.5	11.2	89.1	0.5

Accuracy vs latency on NVIDIA RTX 5070 Ti · PyTorch FP32 for 55 models across 11 families. Highest accuracy: dfine-x at 61.4 mAP@50-95. Fastest is yolox-tiny at 16.2 ms (61.6 FPS).
Model	Family	mAP@50-95 (%)	Latency (ms)	FPS	Params (M)
dfine-x	dfine	61.4	55.1	18.1	62.6
deimv2-x	deimv2	61.3	57.6	17.4	51.2
ec-x	ec	61.1	43.5	23.0	49.9
ec-l	ec	60.1	41.3	24.2	33.0
rtdetrv4-x	rtdetrv4	60.0	60.1	16.6	62.6
dfine-l	dfine	60.0	45.8	21.9	31.2
deim-x	deim	59.6	66.7	15.0	62.6
deimv2-l	deimv2	58.6	50.7	19.7	32.5
rfdetr-l	rfdetr	58.5	39.9	25.1	33.9
ec-m	ec	58.4	37.7	26.5	19.4
rtdetr-x	rtdetr	57.9	46.0	21.8	67.4
deim-l	deim	57.8	53.8	18.6	31.2
dfine-m	dfine	57.8	34.8	28.8	19.6
rtdetrv4-l	rtdetrv4	57.8	40.4	24.7	31.2
rfdetr-m	rfdetr	57.3	33.0	30.3	33.7
yolov9c	yolov9	57.1	23.6	42.3	25.5
rtdetr-r101	rtdetr	56.8	42.4	23.6	76.6
rtdetrv2-r101	rtdetrv2	56.8	39.0	25.7	76.6
rtdetrv4-m	rtdetrv4	56.5	29.8	33.6	19.6
yolox-x	yolox	56.3	25.2	39.6	99.1
yolov9m	yolov9	56.1	26.9	37.1	20.1
deimv2-m	deimv2	56.0	45.4	22.1	18.4
rtdetr-r50	rtdetr	55.9	33.6	29.8	42.9
rtdetr-l	rtdetr	55.8	36.1	27.7	32.9
rtdetrv2-r50	rtdetrv2	55.7	31.1	32.1	42.9
deim-m	deim	55.5	35.3	28.4	19.6
yolox-l	yolox	55.4	23.3	42.8	54.2
rfdetr-s	rfdetr	55.1	27.9	35.8	32.1
rtdetrv2-r50m	rtdetrv2	54.8	25.1	39.9	36.6
ec-s	ec	54.4	36.4	27.5	9.9
rtdetr-r50m	rtdetr	53.8	28.4	35.3	36.6
dfine-s	dfine	53.4	29.3	34.2	10.3
rtdetrv2-r34	rtdetrv2	53.2	24.8	40.4	31.4
deimv2-s	deimv2	53.0	41.2	24.3	9.8
rtdetrv4-s	rtdetrv4	52.9	25.1	39.8	10.3
rtdetr-r34	rtdetr	52.2	24.9	40.2	31.4
deim-s	deim	52.1	30.0	33.4	10.3
yolox-m	yolox	51.7	20.7	48.2	25.3
rfdetr-n	rfdetr	51.4	25.3	39.5	30.5
rtdetrv2-r18	rtdetrv2	50.8	19.6	51.1	20.2
yolov9s	yolov9	50.5	32.5	30.8	7.2
rtdetr-r18	rtdetr	49.8	21.2	47.2	20.2
deim-n	deim	46.8	27.0	37.0	3.8
deimv2-n	deimv2	46.7	28.5	35.1	3.6
dfine-n	dfine	45.8	30.7	32.5	3.8
yolox-s	yolox	44.3	20.0	50.0	9.0
picodet-l	picodet	44.1	25.3	39.5	3.3
deimv2-pico	deimv2	42.3	24.7	40.5	1.5
yolov9t	yolov9	41.8	31.3	31.9	2.0
picodet-m	picodet	37.9	22.2	45.1	2.1
yolox-tiny	yolox	35.5	16.2	61.6	5.1
deimv2-femto	deimv2	34.5	22.1	45.3	1.0
picodet-s	picodet	30.4	20.0	50.0	1.0
yolox-nano	yolox	28.8	18.7	53.6	0.9
deimv2-atto	deimv2	27.5	24.7	40.4	0.5

Accuracy vs latency on Raspberry Pi 5 · PyTorch FP32 for 1 models across 1 families. Highest accuracy: yolov9t at 41.4 mAP@50-95. Fastest is yolov9t at 346.3 ms (2.9 FPS).
Model	Family	mAP@50-95 (%)	Latency (ms)	FPS	Params (M)
yolov9t	yolov9	41.4	346.3	2.9	2.0

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