ResNet18: Optimized for Qualcomm Devices

ResNet18 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 ResNet18 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	w8a8	Universal	QAIRT 2.37, ONNX Runtime 1.23.0	Download
QNN_DLC	float	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 ResNet18 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 ResNet18 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: 11.7M
• Model size (float): 44.6 MB
• Model size (w8a8): 11.3 MB

Performance Summary

Model	Runtime	Precision	Chipset	Inference Time (ms)	Peak Memory Range (MB)	Primary Compute Unit
ResNet18	ONNX	float	Snapdragon® X Elite	1.151 ms	23 - 23 MB	NPU
ResNet18	ONNX	float	Snapdragon® 8 Gen 3 Mobile	0.939 ms	0 - 103 MB	NPU
ResNet18	ONNX	float	Qualcomm® QCS8550 (Proxy)	1.237 ms	0 - 25 MB	NPU
ResNet18	ONNX	float	Qualcomm® QCS9075	2.0 ms	1 - 3 MB	NPU
ResNet18	ONNX	float	Snapdragon® 8 Elite For Galaxy Mobile	0.75 ms	0 - 90 MB	NPU
ResNet18	ONNX	float	Snapdragon® 8 Elite Gen 5 Mobile	0.657 ms	0 - 91 MB	NPU
ResNet18	ONNX	w8a8	Snapdragon® X Elite	0.613 ms	11 - 11 MB	NPU
ResNet18	ONNX	w8a8	Snapdragon® 8 Gen 3 Mobile	0.582 ms	0 - 116 MB	NPU
ResNet18	ONNX	w8a8	Qualcomm® QCS6490	13.761 ms	6 - 24 MB	CPU
ResNet18	ONNX	w8a8	Qualcomm® QCS8550 (Proxy)	0.747 ms	0 - 152 MB	NPU
ResNet18	ONNX	w8a8	Qualcomm® QCS9075	0.858 ms	0 - 3 MB	NPU
ResNet18	ONNX	w8a8	Qualcomm® QCM6690	11.209 ms	6 - 14 MB	CPU
ResNet18	ONNX	w8a8	Snapdragon® 8 Elite For Galaxy Mobile	0.476 ms	0 - 92 MB	NPU
ResNet18	ONNX	w8a8	Snapdragon® 7 Gen 4 Mobile	8.586 ms	8 - 15 MB	CPU
ResNet18	ONNX	w8a8	Snapdragon® 8 Elite Gen 5 Mobile	0.435 ms	0 - 94 MB	NPU
ResNet18	QNN_DLC	float	Snapdragon® X Elite	1.435 ms	1 - 1 MB	NPU
ResNet18	QNN_DLC	float	Snapdragon® 8 Gen 3 Mobile	0.929 ms	0 - 34 MB	NPU
ResNet18	QNN_DLC	float	Qualcomm® QCS8275 (Proxy)	6.004 ms	1 - 24 MB	NPU
ResNet18	QNN_DLC	float	Qualcomm® QCS8550 (Proxy)	1.319 ms	1 - 145 MB	NPU
ResNet18	QNN_DLC	float	Qualcomm® SA8775P	1.981 ms	1 - 27 MB	NPU
ResNet18	QNN_DLC	float	Qualcomm® QCS9075	2.059 ms	1 - 3 MB	NPU
ResNet18	QNN_DLC	float	Qualcomm® QCS8450 (Proxy)	2.432 ms	0 - 37 MB	NPU
ResNet18	QNN_DLC	float	Qualcomm® SA7255P	6.004 ms	1 - 24 MB	NPU
ResNet18	QNN_DLC	float	Qualcomm® SA8295P	2.342 ms	1 - 20 MB	NPU
ResNet18	QNN_DLC	float	Snapdragon® 8 Elite For Galaxy Mobile	0.72 ms	0 - 23 MB	NPU
ResNet18	QNN_DLC	float	Snapdragon® 8 Elite Gen 5 Mobile	0.594 ms	1 - 27 MB	NPU
ResNet18	QNN_DLC	w8a8	Snapdragon® X Elite	0.622 ms	0 - 0 MB	NPU
ResNet18	QNN_DLC	w8a8	Snapdragon® 8 Gen 3 Mobile	0.405 ms	0 - 48 MB	NPU
ResNet18	QNN_DLC	w8a8	Qualcomm® QCS6490	1.811 ms	0 - 2 MB	NPU
ResNet18	QNN_DLC	w8a8	Qualcomm® QCS8275 (Proxy)	1.309 ms	0 - 24 MB	NPU
ResNet18	QNN_DLC	w8a8	Qualcomm® QCS8550 (Proxy)	0.548 ms	0 - 2 MB	NPU
ResNet18	QNN_DLC	w8a8	Qualcomm® SA8775P	0.708 ms	0 - 25 MB	NPU
ResNet18	QNN_DLC	w8a8	Qualcomm® QCS9075	0.61 ms	0 - 2 MB	NPU
ResNet18	QNN_DLC	w8a8	Qualcomm® QCM6690	3.239 ms	0 - 31 MB	NPU
ResNet18	QNN_DLC	w8a8	Qualcomm® QCS8450 (Proxy)	0.743 ms	0 - 48 MB	NPU
ResNet18	QNN_DLC	w8a8	Qualcomm® SA7255P	1.309 ms	0 - 24 MB	NPU
ResNet18	QNN_DLC	w8a8	Qualcomm® SA8295P	0.957 ms	0 - 21 MB	NPU
ResNet18	QNN_DLC	w8a8	Snapdragon® 8 Elite For Galaxy Mobile	0.299 ms	0 - 26 MB	NPU
ResNet18	QNN_DLC	w8a8	Snapdragon® 7 Gen 4 Mobile	0.696 ms	0 - 31 MB	NPU
ResNet18	QNN_DLC	w8a8	Snapdragon® 8 Elite Gen 5 Mobile	0.282 ms	0 - 26 MB	NPU
ResNet18	TFLITE	float	Snapdragon® 8 Gen 3 Mobile	0.924 ms	0 - 63 MB	NPU
ResNet18	TFLITE	float	Qualcomm® QCS8275 (Proxy)	5.96 ms	0 - 27 MB	NPU
ResNet18	TFLITE	float	Qualcomm® QCS8550 (Proxy)	1.317 ms	0 - 5 MB	NPU
ResNet18	TFLITE	float	Qualcomm® SA8775P	1.968 ms	0 - 31 MB	NPU
ResNet18	TFLITE	float	Qualcomm® QCS9075	2.03 ms	0 - 25 MB	NPU
ResNet18	TFLITE	float	Qualcomm® QCS8450 (Proxy)	2.478 ms	0 - 57 MB	NPU
ResNet18	TFLITE	float	Qualcomm® SA7255P	5.96 ms	0 - 27 MB	NPU
ResNet18	TFLITE	float	Qualcomm® SA8295P	2.335 ms	0 - 22 MB	NPU
ResNet18	TFLITE	float	Snapdragon® 8 Elite For Galaxy Mobile	0.735 ms	0 - 25 MB	NPU
ResNet18	TFLITE	float	Snapdragon® 8 Elite Gen 5 Mobile	0.588 ms	0 - 30 MB	NPU
ResNet18	TFLITE	w8a8	Snapdragon® 8 Gen 3 Mobile	0.293 ms	0 - 47 MB	NPU
ResNet18	TFLITE	w8a8	Qualcomm® QCS6490	1.481 ms	0 - 13 MB	NPU
ResNet18	TFLITE	w8a8	Qualcomm® QCS8275 (Proxy)	1.041 ms	0 - 23 MB	NPU
ResNet18	TFLITE	w8a8	Qualcomm® QCS8550 (Proxy)	0.391 ms	0 - 1 MB	NPU
ResNet18	TFLITE	w8a8	Qualcomm® SA8775P	0.555 ms	0 - 25 MB	NPU
ResNet18	TFLITE	w8a8	Qualcomm® QCS9075	0.464 ms	0 - 13 MB	NPU
ResNet18	TFLITE	w8a8	Qualcomm® QCM6690	2.788 ms	0 - 30 MB	NPU
ResNet18	TFLITE	w8a8	Qualcomm® QCS8450 (Proxy)	0.609 ms	0 - 49 MB	NPU
ResNet18	TFLITE	w8a8	Qualcomm® SA7255P	1.041 ms	0 - 23 MB	NPU
ResNet18	TFLITE	w8a8	Qualcomm® SA8295P	0.774 ms	0 - 20 MB	NPU
ResNet18	TFLITE	w8a8	Snapdragon® 8 Elite For Galaxy Mobile	0.246 ms	0 - 21 MB	NPU
ResNet18	TFLITE	w8a8	Snapdragon® 7 Gen 4 Mobile	0.564 ms	0 - 30 MB	NPU
ResNet18	TFLITE	w8a8	Snapdragon® 8 Elite Gen 5 Mobile	0.233 ms	0 - 25 MB	NPU

License

• The license for the original implementation of ResNet18 can be found here.

References

• Deep Residual Learning for Image Recognition
• Source Model Implementation

Community

• Join our AI Hub Slack community to collaborate, post questions and learn more about on-device AI.
• For questions or feedback please reach out to us.