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Jetson AGX Orin 64GB: 63 benchmark rows, 37% measured.

Method v1.0 · dataset 2026-09-07 · verified 2026-09-07 · last updated September 2026

23 of 63 rows are measured and published (class C); the rest are EdgeAIStack-derived (class D). 16 model families. Precisions: FP32 (10), FP16 (29), INT8 (22), INT4 (2). Runtimes: tensorrt (56), mlc (2), pytorch (5). Tasks: detection (48), classification (5), text generation (2), segmentation (3), lidar detection 3d (1), speech recognition (3), pose (1). Jetson AGX Orin 64GB 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.

FamilyFP32FP16INT8INT4
EfficientDet310 fps D395.8 fps D
EfficientNet2800 fps D
Llama163.9 tok/s C
SSD MobileNet512 fps D
MobileSAM25.6 fps C
NanoSAM123.5 fps C
PointPillars25 fps D
ResNet2800 fps D1566 fps C
RetinaNet85.7 fps C85.7 fps C
RT-DETR101 fps D134 fps D
WhisperD
YOLO11254.5 fps C392 fps C459 fps C
YOLO12333 fps D416.5 fps D
YOLOv8371 fps D504 fps D
YOLOv872 fps D
YOLOv895 fps D

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