Beit: Optimized for Qualcomm Devices

Beit 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 Beit 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 2.45, ONNX Runtime 1.27.1	Download
ONNX	w8a16	Universal	QAIRT 2.45, ONNX Runtime 1.27.1	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 Beit 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 Beit 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: 92.0M
• Model size (float): 351 MB

Performance Summary

Model	Runtime	Precision	Chipset	Inference Time (ms)	Peak Memory Range (MB)	Primary Compute Unit
Beit	ONNX	float	Snapdragon® X2 Elite	7.436 ms	2 - 2 MB	NPU
Beit	ONNX	float	Snapdragon® X Elite	15.305 ms	184 - 184 MB	NPU
Beit	ONNX	float	Snapdragon® 8 Gen 3 Mobile	10.496 ms	0 - 449 MB	NPU
Beit	ONNX	float	Snapdragon® 8 Gen 1 Mobile	17.894 ms	1 - 422 MB	NPU
Beit	ONNX	float	Qualcomm® Dragonwing™ QCS8550 (Proxy)	14.88 ms	0 - 194 MB	NPU
Beit	ONNX	float	Qualcomm® QCS8450	17.894 ms	1 - 422 MB	NPU
Beit	ONNX	float	Qualcomm® Dragonwing™ IQ-9075	17.267 ms	0 - 4 MB	NPU
Beit	ONNX	float	Qualcomm® Dragonwing™ IQ-X7181	15.305 ms	184 - 184 MB	NPU
Beit	ONNX	float	Qualcomm® Dragonwing™ Q-8750	8.532 ms	1 - 305 MB	NPU
Beit	ONNX	float	Snapdragon® 8 Elite Mobile	8.532 ms	1 - 305 MB	NPU
Beit	ONNX	float	Snapdragon® 8 Elite Gen 5 Mobile	7.161 ms	0 - 305 MB	NPU
Beit	ONNX	w8a16	Snapdragon® X2 Elite	2.67 ms	1 - 1 MB	NPU
Beit	ONNX	w8a16	Snapdragon® X Elite	6.899 ms	96 - 96 MB	NPU
Beit	ONNX	w8a16	Snapdragon® 8 Gen 3 Mobile	4.572 ms	0 - 422 MB	NPU
Beit	ONNX	w8a16	Snapdragon® 8 Gen 1 Mobile	11.152 ms	0 - 423 MB	NPU
Beit	ONNX	w8a16	Qualcomm® Dragonwing™ QCS6490	36.169 ms	0 - 3 MB	NPU
Beit	ONNX	w8a16	Qualcomm® Dragonwing™ QCS8550 (Proxy)	6.695 ms	0 - 3 MB	NPU
Beit	ONNX	w8a16	Qualcomm® QCS8450	11.152 ms	0 - 423 MB	NPU
Beit	ONNX	w8a16	Qualcomm® Dragonwing™ IQ-9075	6.624 ms	0 - 3 MB	NPU
Beit	ONNX	w8a16	Qualcomm® Dragonwing™ IQ-X7181	6.899 ms	96 - 96 MB	NPU
Beit	ONNX	w8a16	Qualcomm® Dragonwing™ Q-8750	3.578 ms	0 - 362 MB	NPU
Beit	ONNX	w8a16	Snapdragon® 8 Elite Mobile	3.578 ms	0 - 362 MB	NPU
Beit	ONNX	w8a16	Snapdragon® 8 Elite Gen 5 Mobile	2.398 ms	0 - 257 MB	NPU
Beit	QNN_DLC	float	Snapdragon® X2 Elite	7.849 ms	1 - 1 MB	NPU
Beit	QNN_DLC	float	Snapdragon® X Elite	15.125 ms	1 - 1 MB	NPU
Beit	QNN_DLC	float	Snapdragon® 8 Gen 3 Mobile	10.498 ms	0 - 392 MB	NPU
Beit	QNN_DLC	float	Snapdragon® 8 Gen 1 Mobile	17.579 ms	0 - 380 MB	NPU
Beit	QNN_DLC	float	Qualcomm® Dragonwing™ QCS8275	47.915 ms	1 - 295 MB	NPU
Beit	QNN_DLC	float	Qualcomm® Dragonwing™ QCS8550 (Proxy)	14.39 ms	1 - 415 MB	NPU
Beit	QNN_DLC	float	Qualcomm® SA8775P	17.197 ms	1 - 296 MB	NPU
Beit	QNN_DLC	float	Qualcomm® SA8650P	17.197 ms	1 - 296 MB	NPU
Beit	QNN_DLC	float	Qualcomm® SA8255P	17.197 ms	1 - 296 MB	NPU
Beit	QNN_DLC	float	Qualcomm® QCS8450	17.579 ms	0 - 380 MB	NPU
Beit	QNN_DLC	float	Qualcomm® Dragonwing™ IQ-9075	20.102 ms	1 - 3 MB	NPU
Beit	QNN_DLC	float	Qualcomm® Dragonwing™ IQ-X7181	15.125 ms	1 - 1 MB	NPU
Beit	QNN_DLC	float	Qualcomm® Dragonwing™ Q-8750	8.541 ms	1 - 301 MB	NPU
Beit	QNN_DLC	float	Qualcomm® SA7255P	47.915 ms	1 - 295 MB	NPU
Beit	QNN_DLC	float	Qualcomm® SA8295P	15.339 ms	1 - 289 MB	NPU
Beit	QNN_DLC	float	Snapdragon® 8 Elite Mobile	8.541 ms	1 - 301 MB	NPU
Beit	QNN_DLC	float	Snapdragon® 8 Elite Gen 5 Mobile	7.181 ms	1 - 301 MB	NPU
Beit	QNN_DLC	w8a16	Snapdragon® X2 Elite	3.156 ms	0 - 0 MB	NPU
Beit	QNN_DLC	w8a16	Snapdragon® X Elite	7.302 ms	0 - 0 MB	NPU
Beit	QNN_DLC	w8a16	Snapdragon® 8 Gen 3 Mobile	4.65 ms	0 - 409 MB	NPU
Beit	QNN_DLC	w8a16	Qualcomm® Dragonwing™ QCS8275	15.087 ms	0 - 350 MB	NPU
Beit	QNN_DLC	w8a16	Qualcomm® Dragonwing™ QCS8550 (Proxy)	6.776 ms	0 - 266 MB	NPU
Beit	QNN_DLC	w8a16	Qualcomm® SA8775P	7.041 ms	0 - 351 MB	NPU
Beit	QNN_DLC	w8a16	Qualcomm® SA8650P	7.041 ms	0 - 351 MB	NPU
Beit	QNN_DLC	w8a16	Qualcomm® SA8255P	7.041 ms	0 - 351 MB	NPU
Beit	QNN_DLC	w8a16	Qualcomm® Dragonwing™ IQ-9075	6.843 ms	0 - 2 MB	NPU
Beit	QNN_DLC	w8a16	Qualcomm® Dragonwing™ IQ-X7181	7.302 ms	0 - 0 MB	NPU
Beit	QNN_DLC	w8a16	Qualcomm® Dragonwing™ Q-6690	65.256 ms	0 - 428 MB	NPU
Beit	QNN_DLC	w8a16	Qualcomm® Dragonwing™ Q-7790	8.652 ms	0 - 400 MB	NPU
Beit	QNN_DLC	w8a16	Qualcomm® Dragonwing™ Q-8750	3.557 ms	0 - 351 MB	NPU
Beit	QNN_DLC	w8a16	Qualcomm® SA7255P	15.087 ms	0 - 350 MB	NPU
Beit	QNN_DLC	w8a16	Snapdragon® 8 Elite Mobile	3.557 ms	0 - 351 MB	NPU
Beit	QNN_DLC	w8a16	Snapdragon® 8 Elite Gen 5 Mobile	2.554 ms	0 - 244 MB	NPU
Beit	QNN_DLC	w8a16	Snapdragon® 7 Gen 4 Mobile	8.652 ms	0 - 400 MB	NPU
Beit	TFLITE	float	Snapdragon® 8 Gen 3 Mobile	10.452 ms	0 - 404 MB	NPU
Beit	TFLITE	float	Snapdragon® 8 Gen 1 Mobile	17.698 ms	0 - 371 MB	NPU
Beit	TFLITE	float	Qualcomm® Dragonwing™ QCS8275	47.98 ms	0 - 300 MB	NPU
Beit	TFLITE	float	Qualcomm® Dragonwing™ QCS8550 (Proxy)	14.039 ms	0 - 2 MB	NPU
Beit	TFLITE	float	Qualcomm® SA8775P	17.172 ms	0 - 302 MB	NPU
Beit	TFLITE	float	Qualcomm® SA8650P	17.172 ms	0 - 302 MB	NPU
Beit	TFLITE	float	Qualcomm® SA8255P	17.172 ms	0 - 302 MB	NPU
Beit	TFLITE	float	Qualcomm® QCS8450	17.698 ms	0 - 371 MB	NPU
Beit	TFLITE	float	Qualcomm® Dragonwing™ IQ-9075	17.569 ms	0 - 186 MB	NPU
Beit	TFLITE	float	Qualcomm® Dragonwing™ Q-8750	8.545 ms	0 - 309 MB	NPU
Beit	TFLITE	float	Qualcomm® SA7255P	47.98 ms	0 - 300 MB	NPU
Beit	TFLITE	float	Qualcomm® SA8295P	15.33 ms	0 - 293 MB	NPU
Beit	TFLITE	float	Snapdragon® 8 Elite Mobile	8.545 ms	0 - 309 MB	NPU
Beit	TFLITE	float	Snapdragon® 8 Elite Gen 5 Mobile	7.181 ms	0 - 312 MB	NPU

License

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

References

• BEIT: BERT Pre-Training of Image Transformers
• 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.