Jetson Nano Vs. Intel Neural Compute Stick 2

https://devblogs.nvidia.com/jetson-nano-ai-computing/

Table 2 provides full results, including the performance of other platforms like the Raspberry Pi 3, Intel Neural Compute Stick 2, and Google Edge TPU Coral Dev Board:

Table 2. Inference performance results from Jetson Nano, Raspberry Pi 3, Intel Neural Compute Stick 2, and Google Edge TPU Coral Dev Board

Model	Application	Framework	NVIDIA Jetson Nano	Raspberry Pi 3	Raspberry Pi 3 + Intel Neural Compute Stick 2	Google Edge TPU Dev Board
ResNet-50 (224×224)	Classification	TensorFlow	36 FPS	1.4 FPS	16 FPS	DNR
MobileNet-v2 (300×300)	Classification	TensorFlow	64 FPS	2.5 FPS	30 FPS	130 FPS
SSD ResNet-18 (960×544)	Object Detection	TensorFlow	5 FPS	DNR	DNR	DNR
SSD ResNet-18 (480×272)	Object Detection	TensorFlow	16 FPS	DNR	DNR	DNR
SSD ResNet-18 (300×300)	Object Detection	TensorFlow	18 FPS	DNR	DNR	DNR
SSD Mobilenet-V2 (960×544)	Object Detection	TensorFlow	8 FPS	DNR	1.8 FPS	DNR
SSD Mobilenet-V2 (480×272)	Object Detection	TensorFlow	27 FPS	DNR	7 FPS	DNR
SSD Mobilenet-V2 (300×300)	Object Detection	TensorFlow	39 FPS	1 FPS	11 FPS	48 FPS
Inception V4 (299×299)	Classification	PyTorch	11 FPS	DNR	DNR	9 FPS
Tiny YOLO V3 (416×416)	Object Detection	Darknet	25 FPS	0.5 FPS	DNR	DNR
OpenPose (256×256)	Pose Estimation	Caffe	14 FPS	DNR	5 FPS	DNR
VGG-19 (224×224)	Classification	MXNet	10 FPS	0.5 FPS	5 FPS	DNR
Super Resolution (481×321)	Image Processing	PyTorch	15 FPS	DNR	0.6 FPS	DNR
Unet (1x512x512)	Segmentation	Caffe	18 FPS	DNR	5 FPS	DNR