GPUNet: Optimized for Qualcomm Devices

GPUNet is a machine learning model that can classify images from the Imagenet dataset. It can also be used as a backbone in building more complex models for specific use cases.

This is based on the implementation of GPUNet found here. This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the Qualcomm® AI Hub Models library to export with custom configurations. More details on model performance across various devices, can be found here.

Qualcomm AI Hub Models uses Qualcomm AI Hub Workbench to compile, profile, and evaluate this model. Sign up to run these models on a hosted Qualcomm® device.

Getting Started

There are two ways to deploy this model on your device:

Option 1: Download Pre-Exported Models

Below are pre-exported model assets ready for deployment.

Runtime	Precision	Chipset	SDK Versions	Download
ONNX	float	Universal	QAIRT 2.37, ONNX Runtime 1.23.0	Download
ONNX	w8a16	Universal	QAIRT 2.37, ONNX Runtime 1.23.0	Download
ONNX	w8a8	Universal	QAIRT 2.37, ONNX Runtime 1.23.0	Download
QNN_DLC	float	Universal	QAIRT 2.42	Download
QNN_DLC	w8a16	Universal	QAIRT 2.42	Download
QNN_DLC	w8a8	Universal	QAIRT 2.42	Download
TFLITE	float	Universal	QAIRT 2.42, TFLite 2.17.0	Download
TFLITE	w8a8	Universal	QAIRT 2.42, TFLite 2.17.0	Download

For more device-specific assets and performance metrics, visit GPUNet on Qualcomm® AI Hub.

Option 2: Export with Custom Configurations

Use the Qualcomm® AI Hub Models Python library to compile and export the model with your own:

Custom weights (e.g., fine-tuned checkpoints)
Custom input shapes
Target device and runtime configurations

This option is ideal if you need to customize the model beyond the default configuration provided here.

See our repository for GPUNet on GitHub for usage instructions.

Model Details

Model Type: Model_use_case.image_classification

Model Stats:

Model checkpoint: Imagenet
Input resolution: 224x224
Number of parameters: 10.49M
Model size (float): 45.28MB
Model size (w8a8): 21.3MB

Performance Summary

Model	Runtime	Precision	Chipset	Inference Time (ms)	Peak Memory Range (MB)	Primary Compute Unit
GPUNet	ONNX	float	Snapdragon® X Elite	1.12 ms	24 - 24 MB	NPU
GPUNet	ONNX	float	Snapdragon® 8 Gen 3 Mobile	0.955 ms	0 - 126 MB	NPU
GPUNet	ONNX	float	Qualcomm® QCS8550 (Proxy)	1.231 ms	0 - 198 MB	NPU
GPUNet	ONNX	float	Qualcomm® QCS9075	1.509 ms	1 - 3 MB	NPU
GPUNet	ONNX	float	Snapdragon® 8 Elite For Galaxy Mobile	0.739 ms	0 - 99 MB	NPU
GPUNet	ONNX	float	Snapdragon® 8 Elite Gen 5 Mobile	0.636 ms	0 - 99 MB	NPU
GPUNet	ONNX	w8a16	Snapdragon® X Elite	0.974 ms	12 - 12 MB	NPU
GPUNet	ONNX	w8a16	Snapdragon® 8 Gen 3 Mobile	0.777 ms	0 - 131 MB	NPU
GPUNet	ONNX	w8a16	Qualcomm® QCS6490	102.34 ms	18 - 33 MB	CPU
GPUNet	ONNX	w8a16	Qualcomm® QCS8550 (Proxy)	0.995 ms	0 - 25 MB	NPU
GPUNet	ONNX	w8a16	Qualcomm® QCS9075	1.223 ms	0 - 3 MB	NPU
GPUNet	ONNX	w8a16	Qualcomm® QCM6690	53.444 ms	28 - 36 MB	CPU
GPUNet	ONNX	w8a16	Snapdragon® 8 Elite For Galaxy Mobile	0.556 ms	0 - 114 MB	NPU
GPUNet	ONNX	w8a16	Snapdragon® 7 Gen 4 Mobile	40.754 ms	30 - 37 MB	CPU
GPUNet	ONNX	w8a16	Snapdragon® 8 Elite Gen 5 Mobile	0.463 ms	0 - 114 MB	NPU
GPUNet	ONNX	w8a8	Snapdragon® X Elite	0.713 ms	12 - 12 MB	NPU
GPUNet	ONNX	w8a8	Snapdragon® 8 Gen 3 Mobile	0.583 ms	0 - 125 MB	NPU
GPUNet	ONNX	w8a8	Qualcomm® QCS6490	16.722 ms	4 - 18 MB	CPU
GPUNet	ONNX	w8a8	Qualcomm® QCS8550 (Proxy)	0.827 ms	0 - 26 MB	NPU
GPUNet	ONNX	w8a8	Qualcomm® QCS9075	0.947 ms	0 - 3 MB	NPU
GPUNet	ONNX	w8a8	Qualcomm® QCM6690	10.135 ms	11 - 19 MB	CPU
GPUNet	ONNX	w8a8	Snapdragon® 8 Elite For Galaxy Mobile	0.507 ms	0 - 107 MB	NPU
GPUNet	ONNX	w8a8	Snapdragon® 7 Gen 4 Mobile	7.572 ms	9 - 17 MB	CPU
GPUNet	ONNX	w8a8	Snapdragon® 8 Elite Gen 5 Mobile	0.469 ms	0 - 113 MB	NPU
GPUNet	QNN_DLC	float	Snapdragon® X Elite	1.391 ms	1 - 1 MB	NPU
GPUNet	QNN_DLC	float	Snapdragon® 8 Gen 3 Mobile	0.947 ms	0 - 62 MB	NPU
GPUNet	QNN_DLC	float	Qualcomm® QCS8275 (Proxy)	4.721 ms	1 - 33 MB	NPU
GPUNet	QNN_DLC	float	Qualcomm® QCS8550 (Proxy)	1.297 ms	1 - 105 MB	NPU
GPUNet	QNN_DLC	float	Qualcomm® SA8775P	1.713 ms	1 - 36 MB	NPU
GPUNet	QNN_DLC	float	Qualcomm® QCS9075	1.569 ms	1 - 3 MB	NPU
GPUNet	QNN_DLC	float	Qualcomm® QCS8450 (Proxy)	2.408 ms	0 - 64 MB	NPU
GPUNet	QNN_DLC	float	Qualcomm® SA7255P	4.721 ms	1 - 33 MB	NPU
GPUNet	QNN_DLC	float	Qualcomm® SA8295P	2.283 ms	0 - 33 MB	NPU
GPUNet	QNN_DLC	float	Snapdragon® 8 Elite For Galaxy Mobile	0.707 ms	0 - 32 MB	NPU
GPUNet	QNN_DLC	float	Snapdragon® 8 Elite Gen 5 Mobile	0.565 ms	1 - 37 MB	NPU
GPUNet	QNN_DLC	w8a16	Snapdragon® X Elite	1.234 ms	0 - 0 MB	NPU
GPUNet	QNN_DLC	w8a16	Snapdragon® 8 Gen 3 Mobile	0.768 ms	0 - 57 MB	NPU
GPUNet	QNN_DLC	w8a16	Qualcomm® QCS6490	3.257 ms	2 - 4 MB	NPU
GPUNet	QNN_DLC	w8a16	Qualcomm® QCS8275 (Proxy)	2.494 ms	0 - 41 MB	NPU
GPUNet	QNN_DLC	w8a16	Qualcomm® QCS8550 (Proxy)	1.065 ms	0 - 2 MB	NPU
GPUNet	QNN_DLC	w8a16	Qualcomm® SA8775P	1.293 ms	0 - 43 MB	NPU
GPUNet	QNN_DLC	w8a16	Qualcomm® QCS9075	1.226 ms	2 - 4 MB	NPU
GPUNet	QNN_DLC	w8a16	Qualcomm® QCM6690	6.566 ms	0 - 160 MB	NPU
GPUNet	QNN_DLC	w8a16	Qualcomm® QCS8450 (Proxy)	1.458 ms	0 - 61 MB	NPU
GPUNet	QNN_DLC	w8a16	Qualcomm® SA7255P	2.494 ms	0 - 41 MB	NPU
GPUNet	QNN_DLC	w8a16	Qualcomm® SA8295P	1.656 ms	0 - 39 MB	NPU
GPUNet	QNN_DLC	w8a16	Snapdragon® 8 Elite For Galaxy Mobile	0.528 ms	0 - 40 MB	NPU
GPUNet	QNN_DLC	w8a16	Snapdragon® 7 Gen 4 Mobile	1.284 ms	0 - 42 MB	NPU
GPUNet	QNN_DLC	w8a16	Snapdragon® 8 Elite Gen 5 Mobile	0.434 ms	0 - 45 MB	NPU
GPUNet	QNN_DLC	w8a8	Snapdragon® X Elite	0.732 ms	0 - 0 MB	NPU
GPUNet	QNN_DLC	w8a8	Snapdragon® 8 Gen 3 Mobile	0.452 ms	0 - 56 MB	NPU
GPUNet	QNN_DLC	w8a8	Qualcomm® QCS6490	1.969 ms	0 - 2 MB	NPU
GPUNet	QNN_DLC	w8a8	Qualcomm® QCS8275 (Proxy)	1.427 ms	0 - 39 MB	NPU
GPUNet	QNN_DLC	w8a8	Qualcomm® QCS8550 (Proxy)	0.607 ms	0 - 3 MB	NPU
GPUNet	QNN_DLC	w8a8	Qualcomm® SA8775P	0.797 ms	0 - 40 MB	NPU
GPUNet	QNN_DLC	w8a8	Qualcomm® QCS9075	0.691 ms	0 - 2 MB	NPU
GPUNet	QNN_DLC	w8a8	Qualcomm® QCM6690	3.448 ms	0 - 42 MB	NPU
GPUNet	QNN_DLC	w8a8	Qualcomm® QCS8450 (Proxy)	0.846 ms	0 - 58 MB	NPU
GPUNet	QNN_DLC	w8a8	Qualcomm® SA7255P	1.427 ms	0 - 39 MB	NPU
GPUNet	QNN_DLC	w8a8	Qualcomm® SA8295P	1.073 ms	0 - 37 MB	NPU
GPUNet	QNN_DLC	w8a8	Snapdragon® 8 Elite For Galaxy Mobile	0.338 ms	0 - 37 MB	NPU
GPUNet	QNN_DLC	w8a8	Snapdragon® 7 Gen 4 Mobile	0.794 ms	0 - 38 MB	NPU
GPUNet	QNN_DLC	w8a8	Snapdragon® 8 Elite Gen 5 Mobile	0.294 ms	0 - 44 MB	NPU
GPUNet	TFLITE	float	Snapdragon® 8 Gen 3 Mobile	0.941 ms	0 - 97 MB	NPU
GPUNet	TFLITE	float	Qualcomm® QCS8275 (Proxy)	4.701 ms	0 - 63 MB	NPU
GPUNet	TFLITE	float	Qualcomm® QCS8550 (Proxy)	1.275 ms	0 - 3 MB	NPU
GPUNet	TFLITE	float	Qualcomm® SA8775P	7.192 ms	0 - 63 MB	NPU
GPUNet	TFLITE	float	Qualcomm® QCS9075	1.574 ms	0 - 27 MB	NPU
GPUNet	TFLITE	float	Qualcomm® QCS8450 (Proxy)	2.401 ms	0 - 93 MB	NPU
GPUNet	TFLITE	float	Qualcomm® SA7255P	4.701 ms	0 - 63 MB	NPU
GPUNet	TFLITE	float	Qualcomm® SA8295P	2.255 ms	0 - 62 MB	NPU
GPUNet	TFLITE	float	Snapdragon® 8 Elite For Galaxy Mobile	0.713 ms	0 - 61 MB	NPU
GPUNet	TFLITE	float	Snapdragon® 8 Elite Gen 5 Mobile	0.564 ms	0 - 66 MB	NPU
GPUNet	TFLITE	w8a8	Snapdragon® 8 Gen 3 Mobile	0.34 ms	0 - 54 MB	NPU
GPUNet	TFLITE	w8a8	Qualcomm® QCS6490	1.649 ms	0 - 15 MB	NPU
GPUNet	TFLITE	w8a8	Qualcomm® QCS8275 (Proxy)	1.12 ms	0 - 37 MB	NPU
GPUNet	TFLITE	w8a8	Qualcomm® QCS8550 (Proxy)	0.422 ms	0 - 2 MB	NPU
GPUNet	TFLITE	w8a8	Qualcomm® SA8775P	0.62 ms	0 - 40 MB	NPU
GPUNet	TFLITE	w8a8	Qualcomm® QCS9075	0.524 ms	0 - 14 MB	NPU
GPUNet	TFLITE	w8a8	Qualcomm® QCM6690	2.998 ms	0 - 39 MB	NPU
GPUNet	TFLITE	w8a8	Qualcomm® QCS8450 (Proxy)	0.685 ms	0 - 55 MB	NPU
GPUNet	TFLITE	w8a8	Qualcomm® SA7255P	1.12 ms	0 - 37 MB	NPU
GPUNet	TFLITE	w8a8	Qualcomm® SA8295P	0.865 ms	0 - 35 MB	NPU
GPUNet	TFLITE	w8a8	Snapdragon® 8 Elite For Galaxy Mobile	0.276 ms	0 - 36 MB	NPU
GPUNet	TFLITE	w8a8	Snapdragon® 7 Gen 4 Mobile	0.627 ms	0 - 36 MB	NPU
GPUNet	TFLITE	w8a8	Snapdragon® 8 Elite Gen 5 Mobile	0.237 ms	0 - 43 MB	NPU

License

The license for the original implementation of GPUNet can be found here.

References

Community

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Paper for qualcomm/GPUNet

GPUNet: Searching the Deployable Convolution Neural Networks for GPUs

Paper • 2205.00841 • Published Apr 26, 2022