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 1.24.3	Download
ONNX	w8a16	Universal	QAIRT 2.42, ONNX Runtime 1.24.3	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	7.842 ms	1 - 534 MB	NPU
Swin-Base	ONNX	float	Snapdragon® 8 Elite Mobile	9.783 ms	0 - 511 MB	NPU
Swin-Base	ONNX	float	Snapdragon® X2 Elite	8.376 ms	175 - 175 MB	NPU
Swin-Base	ONNX	float	Snapdragon® X Elite	19.682 ms	174 - 174 MB	NPU
Swin-Base	ONNX	float	Snapdragon® X Elite	19.682 ms	174 - 174 MB	NPU
Swin-Base	ONNX	float	Snapdragon® 8 Gen 3 Mobile	13.052 ms	1 - 608 MB	NPU
Swin-Base	ONNX	float	Qualcomm® QCS8550 (Proxy)	18.905 ms	0 - 196 MB	NPU
Swin-Base	ONNX	float	Snapdragon® 8 Elite For Galaxy Mobile	9.783 ms	0 - 511 MB	NPU
Swin-Base	ONNX	float	Qualcomm® QCS9075	24.452 ms	0 - 4 MB	NPU
Swin-Base	ONNX	w8a16	Snapdragon® 8 Elite Gen 5 Mobile	6.969 ms	0 - 448 MB	NPU
Swin-Base	ONNX	w8a16	Snapdragon® 8 Elite Mobile	8.785 ms	0 - 424 MB	NPU
Swin-Base	ONNX	w8a16	Snapdragon® X2 Elite	7.518 ms	92 - 92 MB	NPU
Swin-Base	ONNX	w8a16	Snapdragon® X Elite	17.605 ms	91 - 91 MB	NPU
Swin-Base	ONNX	w8a16	Snapdragon® X Elite	17.605 ms	91 - 91 MB	NPU
Swin-Base	ONNX	w8a16	Snapdragon® 8 Gen 3 Mobile	11.385 ms	0 - 554 MB	NPU
Swin-Base	ONNX	w8a16	Qualcomm® QCS6490	1114.666 ms	62 - 92 MB	CPU
Swin-Base	ONNX	w8a16	Qualcomm® QCS8550 (Proxy)	16.751 ms	0 - 112 MB	NPU
Swin-Base	ONNX	w8a16	Snapdragon® 8 Elite For Galaxy Mobile	8.785 ms	0 - 424 MB	NPU
Swin-Base	ONNX	w8a16	Snapdragon® 7 Gen 4 Mobile	592.566 ms	129 - 151 MB	CPU
Swin-Base	ONNX	w8a16	Qualcomm® QCM6690	627.859 ms	129 - 151 MB	CPU
Swin-Base	ONNX	w8a16	Qualcomm® QCS9075	20.874 ms	0 - 3 MB	NPU
Swin-Base	ONNX	w8a16	Snapdragon® 7 Gen 4 Mobile	592.566 ms	129 - 151 MB	CPU
Swin-Base	QNN_DLC	float	Snapdragon® 8 Elite Gen 5 Mobile	7.481 ms	1 - 382 MB	NPU
Swin-Base	QNN_DLC	float	Snapdragon® 8 Elite Mobile	9.423 ms	1 - 366 MB	NPU
Swin-Base	QNN_DLC	float	Snapdragon® X2 Elite	8.482 ms	1 - 1 MB	NPU
Swin-Base	QNN_DLC	float	Snapdragon® X Elite	19.219 ms	1 - 1 MB	NPU
Swin-Base	QNN_DLC	float	Snapdragon® X Elite	19.219 ms	1 - 1 MB	NPU
Swin-Base	QNN_DLC	float	Snapdragon® 8 Gen 3 Mobile	12.409 ms	0 - 515 MB	NPU
Swin-Base	QNN_DLC	float	Qualcomm® QCS8550 (Proxy)	18.341 ms	1 - 2 MB	NPU
Swin-Base	QNN_DLC	float	Qualcomm® SA8775P	21.382 ms	1 - 362 MB	NPU
Swin-Base	QNN_DLC	float	Qualcomm® SA8775P	21.382 ms	1 - 362 MB	NPU
Swin-Base	QNN_DLC	float	Qualcomm® SA8775P	21.382 ms	1 - 362 MB	NPU
Swin-Base	QNN_DLC	float	Qualcomm® SA7255P	53.592 ms	1 - 362 MB	NPU
Swin-Base	QNN_DLC	float	Qualcomm® QCS8450 (Proxy)	29.1 ms	0 - 505 MB	NPU
Swin-Base	QNN_DLC	float	Qualcomm® SA8295P	27.631 ms	1 - 353 MB	NPU
Swin-Base	QNN_DLC	float	Snapdragon® 8 Elite For Galaxy Mobile	9.423 ms	1 - 366 MB	NPU
Swin-Base	QNN_DLC	float	Qualcomm® QCS9075	23.277 ms	1 - 3 MB	NPU
Swin-Base	QNN_DLC	w8a16	Snapdragon® 8 Elite Gen 5 Mobile	7.546 ms	0 - 417 MB	NPU
Swin-Base	QNN_DLC	w8a16	Snapdragon® 8 Elite Mobile	9.567 ms	0 - 406 MB	NPU
Swin-Base	QNN_DLC	w8a16	Snapdragon® X2 Elite	8.441 ms	0 - 0 MB	NPU
Swin-Base	QNN_DLC	w8a16	Snapdragon® X Elite	20.32 ms	0 - 0 MB	NPU
Swin-Base	QNN_DLC	w8a16	Snapdragon® X Elite	20.32 ms	0 - 0 MB	NPU
Swin-Base	QNN_DLC	w8a16	Snapdragon® 8 Gen 3 Mobile	12.838 ms	0 - 508 MB	NPU
Swin-Base	QNN_DLC	w8a16	Qualcomm® QCS8550 (Proxy)	19.074 ms	0 - 349 MB	NPU
Swin-Base	QNN_DLC	w8a16	Qualcomm® SA8775P	19.545 ms	0 - 411 MB	NPU
Swin-Base	QNN_DLC	w8a16	Qualcomm® SA8775P	19.545 ms	0 - 411 MB	NPU
Swin-Base	QNN_DLC	w8a16	Qualcomm® SA8775P	19.545 ms	0 - 411 MB	NPU
Swin-Base	QNN_DLC	w8a16	Qualcomm® SA7255P	35.255 ms	0 - 411 MB	NPU
Swin-Base	QNN_DLC	w8a16	Snapdragon® 8 Elite For Galaxy Mobile	9.567 ms	0 - 406 MB	NPU
Swin-Base	QNN_DLC	w8a16	Snapdragon® 7 Gen 4 Mobile	21.538 ms	0 - 610 MB	NPU
Swin-Base	QNN_DLC	w8a16	Qualcomm® QCM6690	119.434 ms	0 - 913 MB	NPU
Swin-Base	QNN_DLC	w8a16	Qualcomm® QCS9075	22.716 ms	0 - 2 MB	NPU
Swin-Base	QNN_DLC	w8a16	Snapdragon® 7 Gen 4 Mobile	21.538 ms	0 - 610 MB	NPU
Swin-Base	TFLITE	float	Snapdragon® 8 Elite Gen 5 Mobile	7.881 ms	0 - 393 MB	NPU
Swin-Base	TFLITE	float	Snapdragon® 8 Elite Mobile	9.681 ms	0 - 379 MB	NPU
Swin-Base	TFLITE	float	Snapdragon® 8 Gen 3 Mobile	12.779 ms	0 - 1043 MB	NPU
Swin-Base	TFLITE	float	Qualcomm® QCS8550 (Proxy)	18.916 ms	0 - 4 MB	NPU
Swin-Base	TFLITE	float	Qualcomm® SA8775P	21.917 ms	0 - 375 MB	NPU
Swin-Base	TFLITE	float	Qualcomm® SA8775P	21.917 ms	0 - 375 MB	NPU
Swin-Base	TFLITE	float	Qualcomm® SA8775P	21.917 ms	0 - 375 MB	NPU
Swin-Base	TFLITE	float	Qualcomm® SA7255P	53.453 ms	0 - 709 MB	NPU
Swin-Base	TFLITE	float	Qualcomm® QCS8450 (Proxy)	29.021 ms	0 - 509 MB	NPU
Swin-Base	TFLITE	float	Qualcomm® SA8295P	28.384 ms	0 - 371 MB	NPU
Swin-Base	TFLITE	float	Snapdragon® 8 Elite For Galaxy Mobile	9.681 ms	0 - 379 MB	NPU
Swin-Base	TFLITE	float	Qualcomm® QCS9075	23.89 ms	0 - 178 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.