Jetson Orin NX 16GB: 50 benchmark rows, 44% measured.

Method v1.4.1 · dataset 2026-09-29 · verified 2026-09-16 · last updated September 2026

22 of 50 rows are measured and published (class C); the rest are EdgeAIStack-derived (class D). 15 model families. Precisions: FP32 (4), FP16 (31), INT8 (15). Runtimes: tensorrt (50). Tasks: detection (39), classification (4), lidar detection 3d (1), speech recognition (2), pose (3), segmentation (1). Jetson Orin NX 16GB platform page.

Family × precision: best value

The fastest matching row per family and precision (fps, or tokens/s for language models), with its evidence class. Click a cell for the full breakdown.

Family	FP32	FP16	INT8
EfficientDet	—	—	248 fps D
MobileNetV2	—	1250 fps D	—
MobileNetV3	—	1420 fps D	—
PointPillars	—	14 fps D	—
ResNet	—	1180 fps D	1681.9 fps C
RetinaNet	—	21 fps C	—
RT-DETR	—	46.5 fps D	61.9 fps D
Whisper	—	— D	—
YOLO11	95 fps C	211 fps C	256 fps C
YOLO11	—	306.2 fps C	—
YOLO12	—	178.7 fps D	218 fps D
YOLOv8	—	193 fps C	264 fps C
YOLOv8	—	175 fps D	—
YOLOv8	—	160 fps D	—
YOLOv9	—	195 fps D	—

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Jetson Orin NX 16GB: 50 benchmark rows, 44% measured.

Family × precision: best value

Every model on Jetson Orin NX 16GB

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