Swin-Base: Optimized for Qualcomm Devices

SwinBase 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 Swin-Base 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 2.42, ONNX Runtime 1.25.0	Download
ONNX	w8a16	Universal	QAIRT 2.42, ONNX Runtime 1.25.0	Download
QNN_DLC	float	Universal	QAIRT 2.45	Download
QNN_DLC	w8a16	Universal	QAIRT 2.45	Download
TFLITE	float	Universal	QAIRT 2.45	Download

For more device-specific assets and performance metrics, visit Swin-Base 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 Swin-Base 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: 88.8M
• Model size (float): 339 MB
• Model size (w8a16): 90.2 MB

Performance Summary

Model	Runtime	Precision	Chipset	Inference Time (ms)	Peak Memory Range (MB)	Primary Compute Unit
Swin-Base	ONNX	float	Snapdragon® 8 Elite Gen 5 Mobile	7.85 ms	1 - 476 MB	NPU
Swin-Base	ONNX	float	Snapdragon® X2 Elite	8.301 ms	180 - 180 MB	NPU
Swin-Base	ONNX	float	Snapdragon® X Elite	19.221 ms	174 - 174 MB	NPU
Swin-Base	ONNX	float	Snapdragon® 8 Gen 3 Mobile	12.794 ms	1 - 573 MB	NPU
Swin-Base	ONNX	float	Qualcomm® QCS8550 (Proxy)	18.894 ms	0 - 196 MB	NPU
Swin-Base	ONNX	float	Snapdragon® 8 Elite For Galaxy Mobile	9.63 ms	1 - 457 MB	NPU
Swin-Base	ONNX	float	Qualcomm® QCS9075	23.783 ms	1 - 46 MB	NPU
Swin-Base	ONNX	float	Qualcomm® QCS8750	9.63 ms	1 - 457 MB	NPU
Swin-Base	ONNX	float	Qualcomm® QCS7181	19.221 ms	174 - 174 MB	NPU
Swin-Base	ONNX	w8a16	Snapdragon® 8 Elite Gen 5 Mobile	6.982 ms	0 - 441 MB	NPU
Swin-Base	ONNX	w8a16	Snapdragon® X2 Elite	9.139 ms	211 - 211 MB	NPU
Swin-Base	ONNX	w8a16	Snapdragon® X Elite	17.526 ms	149 - 149 MB	NPU
Swin-Base	ONNX	w8a16	Snapdragon® 8 Gen 3 Mobile	11.359 ms	0 - 558 MB	NPU
Swin-Base	ONNX	w8a16	Qualcomm® QCS6490	1096.262 ms	67 - 91 MB	CPU
Swin-Base	ONNX	w8a16	Qualcomm® QCS8550 (Proxy)	16.672 ms	0 - 133 MB	NPU
Swin-Base	ONNX	w8a16	Qualcomm® QCM6690	612.962 ms	128 - 151 MB	CPU
Swin-Base	ONNX	w8a16	Snapdragon® 7 Gen 4 Mobile	582.596 ms	110 - 133 MB	CPU
Swin-Base	ONNX	w8a16	Snapdragon® 8 Elite For Galaxy Mobile	8.796 ms	0 - 423 MB	NPU
Swin-Base	ONNX	w8a16	Qualcomm® QCS9075	20.443 ms	0 - 45 MB	NPU
Swin-Base	ONNX	w8a16	Qualcomm® QCS7790	582.596 ms	110 - 133 MB	CPU
Swin-Base	ONNX	w8a16	Qualcomm® QCS8750	8.796 ms	0 - 423 MB	NPU
Swin-Base	ONNX	w8a16	Qualcomm® QCS7181	17.526 ms	149 - 149 MB	NPU
Swin-Base	QNN_DLC	float	Snapdragon® 8 Elite Gen 5 Mobile	7.491 ms	1 - 382 MB	NPU
Swin-Base	QNN_DLC	float	Snapdragon® X2 Elite	8.51 ms	1 - 1 MB	NPU
Swin-Base	QNN_DLC	float	Snapdragon® X Elite	19.282 ms	1 - 1 MB	NPU
Swin-Base	QNN_DLC	float	Snapdragon® 8 Gen 3 Mobile	12.492 ms	1 - 519 MB	NPU
Swin-Base	QNN_DLC	float	Qualcomm® QCS8550 (Proxy)	18.539 ms	1 - 3 MB	NPU
Swin-Base	QNN_DLC	float	Qualcomm® SA8775P	21.385 ms	1 - 363 MB	NPU
Swin-Base	QNN_DLC	float	Qualcomm® SA8650P	21.385 ms	1 - 363 MB	NPU
Swin-Base	QNN_DLC	float	Qualcomm® SA8255P	21.385 ms	1 - 363 MB	NPU
Swin-Base	QNN_DLC	float	Qualcomm® QCS8450 (Proxy)	29.136 ms	0 - 507 MB	NPU
Swin-Base	QNN_DLC	float	Qualcomm® SA8295P	27.586 ms	1 - 354 MB	NPU
Swin-Base	QNN_DLC	float	Snapdragon® 8 Elite For Galaxy Mobile	9.395 ms	0 - 363 MB	NPU
Swin-Base	QNN_DLC	float	Qualcomm® QCS9075	23.476 ms	3 - 5 MB	NPU
Swin-Base	QNN_DLC	float	Qualcomm® QCS8750	9.395 ms	0 - 363 MB	NPU
Swin-Base	QNN_DLC	float	Qualcomm® QCS7181	19.282 ms	1 - 1 MB	NPU
Swin-Base	QNN_DLC	w8a16	Snapdragon® 8 Elite Gen 5 Mobile	7.559 ms	0 - 416 MB	NPU
Swin-Base	QNN_DLC	w8a16	Snapdragon® X2 Elite	8.434 ms	0 - 0 MB	NPU
Swin-Base	QNN_DLC	w8a16	Snapdragon® X Elite	20.299 ms	0 - 0 MB	NPU
Swin-Base	QNN_DLC	w8a16	Snapdragon® 8 Gen 3 Mobile	12.774 ms	0 - 507 MB	NPU
Swin-Base	QNN_DLC	w8a16	Qualcomm® QCS8275	35.31 ms	0 - 412 MB	NPU
Swin-Base	QNN_DLC	w8a16	Qualcomm® QCS8550 (Proxy)	19.281 ms	0 - 3 MB	NPU
Swin-Base	QNN_DLC	w8a16	Qualcomm® SA8775P	19.541 ms	0 - 413 MB	NPU
Swin-Base	QNN_DLC	w8a16	Qualcomm® SA8650P	19.541 ms	0 - 413 MB	NPU
Swin-Base	QNN_DLC	w8a16	Qualcomm® SA8255P	19.541 ms	0 - 413 MB	NPU
Swin-Base	QNN_DLC	w8a16	Qualcomm® QCM6690	114.422 ms	0 - 928 MB	NPU
Swin-Base	QNN_DLC	w8a16	Qualcomm® SA7255P	35.31 ms	0 - 412 MB	NPU
Swin-Base	QNN_DLC	w8a16	Snapdragon® 7 Gen 4 Mobile	21.574 ms	0 - 603 MB	NPU
Swin-Base	QNN_DLC	w8a16	Snapdragon® 8 Elite For Galaxy Mobile	9.509 ms	0 - 405 MB	NPU
Swin-Base	QNN_DLC	w8a16	Qualcomm® QCS9075	22.522 ms	0 - 2 MB	NPU
Swin-Base	QNN_DLC	w8a16	Qualcomm® QCS7790	21.574 ms	0 - 603 MB	NPU
Swin-Base	QNN_DLC	w8a16	Qualcomm® QCS8750	9.509 ms	0 - 405 MB	NPU
Swin-Base	QNN_DLC	w8a16	Qualcomm® QCS7181	20.299 ms	0 - 0 MB	NPU
Swin-Base	TFLITE	float	Snapdragon® 8 Elite Gen 5 Mobile	7.892 ms	0 - 392 MB	NPU
Swin-Base	TFLITE	float	Snapdragon® 8 Gen 3 Mobile	12.737 ms	0 - 1052 MB	NPU
Swin-Base	TFLITE	float	Qualcomm® QCS8275	53.467 ms	0 - 706 MB	NPU
Swin-Base	TFLITE	float	Qualcomm® QCS8550 (Proxy)	18.932 ms	0 - 3 MB	NPU
Swin-Base	TFLITE	float	Qualcomm® SA8775P	21.942 ms	0 - 378 MB	NPU
Swin-Base	TFLITE	float	Qualcomm® SA8650P	21.942 ms	0 - 378 MB	NPU
Swin-Base	TFLITE	float	Qualcomm® SA8255P	21.942 ms	0 - 378 MB	NPU
Swin-Base	TFLITE	float	Qualcomm® QCS8450 (Proxy)	29.057 ms	0 - 510 MB	NPU
Swin-Base	TFLITE	float	Qualcomm® SA8295P	28.321 ms	0 - 371 MB	NPU
Swin-Base	TFLITE	float	Snapdragon® 8 Elite For Galaxy Mobile	9.726 ms	0 - 387 MB	NPU
Swin-Base	TFLITE	float	Qualcomm® QCS9075	23.904 ms	0 - 178 MB	NPU
Swin-Base	TFLITE	float	Qualcomm® SA7255P	53.467 ms	0 - 706 MB	NPU
Swin-Base	TFLITE	float	Qualcomm® QCS8750	9.726 ms	0 - 387 MB	NPU

License

• The license for the original implementation of Swin-Base can be found here.

References

• Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
• 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.