EfficientViT-b2-cls: Optimized for Qualcomm Devices

EfficientViT 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 EfficientViT-b2-cls 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 2.50, ONNX Runtime 1.30.0	Download
ONNX	w8a16	Universal	QAIRT 2.50, ONNX Runtime 1.30.0	Download
QNN_DLC	float	Universal	QAIRT 2.50	Download
QNN_DLC	w8a16	Universal	QAIRT 2.50	Download
TFLITE	float	Universal	QAIRT 2.50	Download

For more device-specific assets and performance metrics, visit EfficientViT-b2-cls 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 EfficientViT-b2-cls on GitHub for usage instructions.

Model Details

Model Type: Model_use_case.image_classification

Model Stats:

Input resolution: 224x224
Model checkpoint: Imagenet
Model size (float): 92.9 MB
Number of parameters: 24.3M

Performance Summary

Model	Runtime	Precision	Chipset	Inference Time (ms)	Peak Memory Range (MB)	Primary Compute Unit
EfficientViT-b2-cls	ONNX	float	Snapdragon® 8 Elite Gen 5 For Galaxy Mobile	2.433 ms	1 - 76 MB	NPU
EfficientViT-b2-cls	ONNX	float	Snapdragon® 8 Elite For Galaxy Mobile	2.711 ms	0 - 73 MB	NPU
EfficientViT-b2-cls	ONNX	float	Snapdragon® X2 Elite	2.524 ms	2 - 2 MB	NPU
EfficientViT-b2-cls	ONNX	float	Snapdragon® X Elite	5.048 ms	49 - 49 MB	NPU
EfficientViT-b2-cls	ONNX	float	Snapdragon® 8 Gen 3 Mobile	3.224 ms	0 - 150 MB	NPU
EfficientViT-b2-cls	ONNX	float	Snapdragon® 8 Gen 1 Mobile	5.639 ms	1 - 147 MB	NPU
EfficientViT-b2-cls	ONNX	float	Qualcomm® Dragonwing™ IQ-8275	5.094 ms	0 - 5 MB	NPU
EfficientViT-b2-cls	ONNX	float	Qualcomm® Dragonwing™ QCS8550 (Proxy)	4.891 ms	0 - 58 MB	NPU
EfficientViT-b2-cls	ONNX	float	Qualcomm® QCS8450	5.639 ms	1 - 147 MB	NPU
EfficientViT-b2-cls	ONNX	float	Qualcomm® Dragonwing™ IQ-9075	5.595 ms	1 - 4 MB	NPU
EfficientViT-b2-cls	ONNX	float	Qualcomm® Dragonwing™ IQ-X7181	5.048 ms	49 - 49 MB	NPU
EfficientViT-b2-cls	ONNX	float	Qualcomm® Dragonwing™ Q-8750	2.711 ms	0 - 73 MB	NPU
EfficientViT-b2-cls	ONNX	w8a16	Snapdragon® 8 Elite Gen 5 For Galaxy Mobile	2.091 ms	0 - 122 MB	NPU
EfficientViT-b2-cls	ONNX	w8a16	Snapdragon® 8 Elite For Galaxy Mobile	2.433 ms	0 - 120 MB	NPU
EfficientViT-b2-cls	ONNX	w8a16	Snapdragon® X2 Elite	2.228 ms	1 - 1 MB	NPU
EfficientViT-b2-cls	ONNX	w8a16	Snapdragon® X Elite	4.671 ms	26 - 26 MB	NPU
EfficientViT-b2-cls	ONNX	w8a16	Snapdragon® 8 Gen 3 Mobile	3.004 ms	0 - 163 MB	NPU
EfficientViT-b2-cls	ONNX	w8a16	Snapdragon® 8 Gen 1 Mobile	5.333 ms	0 - 176 MB	NPU
EfficientViT-b2-cls	ONNX	w8a16	Qualcomm® Dragonwing™ QCS6490	11.04 ms	0 - 4 MB	NPU
EfficientViT-b2-cls	ONNX	w8a16	Qualcomm® Dragonwing™ IQ-8275	4.078 ms	0 - 4 MB	NPU
EfficientViT-b2-cls	ONNX	w8a16	Qualcomm® Dragonwing™ QCS8550 (Proxy)	4.477 ms	0 - 185 MB	NPU
EfficientViT-b2-cls	ONNX	w8a16	Qualcomm® QCS8450	5.333 ms	0 - 176 MB	NPU
EfficientViT-b2-cls	ONNX	w8a16	Qualcomm® Dragonwing™ IQ-9075	4.762 ms	0 - 4 MB	NPU
EfficientViT-b2-cls	ONNX	w8a16	Qualcomm® Dragonwing™ IQ-X7181	4.671 ms	26 - 26 MB	NPU
EfficientViT-b2-cls	ONNX	w8a16	Qualcomm® Dragonwing™ Q-6690	17.239 ms	0 - 239 MB	NPU
EfficientViT-b2-cls	ONNX	w8a16	Qualcomm® Dragonwing™ Q-7790	4.797 ms	0 - 233 MB	NPU
EfficientViT-b2-cls	ONNX	w8a16	Qualcomm® Dragonwing™ Q-8750	2.433 ms	0 - 120 MB	NPU
EfficientViT-b2-cls	ONNX	w8a16	Snapdragon® 7 Gen 4 Mobile	4.797 ms	0 - 233 MB	NPU
EfficientViT-b2-cls	QNN_DLC	float	Snapdragon® 8 Elite Gen 5 For Galaxy Mobile	2.077 ms	1 - 72 MB	NPU
EfficientViT-b2-cls	QNN_DLC	float	Snapdragon® 8 Elite For Galaxy Mobile	2.368 ms	1 - 70 MB	NPU
EfficientViT-b2-cls	QNN_DLC	float	Snapdragon® X2 Elite	2.49 ms	1 - 1 MB	NPU
EfficientViT-b2-cls	QNN_DLC	float	Snapdragon® X Elite	4.853 ms	1 - 1 MB	NPU
EfficientViT-b2-cls	QNN_DLC	float	Snapdragon® 8 Gen 3 Mobile	2.963 ms	0 - 140 MB	NPU
EfficientViT-b2-cls	QNN_DLC	float	Snapdragon® 8 Gen 1 Mobile	5.878 ms	0 - 145 MB	NPU
EfficientViT-b2-cls	QNN_DLC	float	Qualcomm® Dragonwing™ IQ-8275	4.614 ms	1 - 4 MB	NPU
EfficientViT-b2-cls	QNN_DLC	float	Qualcomm® Dragonwing™ QCS8550 (Proxy)	4.502 ms	1 - 3 MB	NPU
EfficientViT-b2-cls	QNN_DLC	float	Qualcomm® SA8650P	6.803 ms	1 - 69 MB	NPU
EfficientViT-b2-cls	QNN_DLC	float	Qualcomm® SA8255P	6.803 ms	1 - 69 MB	NPU
EfficientViT-b2-cls	QNN_DLC	float	Qualcomm® QCS8450	5.878 ms	0 - 145 MB	NPU
EfficientViT-b2-cls	QNN_DLC	float	Qualcomm® Dragonwing™ IQ-9075	5.157 ms	3 - 5 MB	NPU
EfficientViT-b2-cls	QNN_DLC	float	Qualcomm® Dragonwing™ IQ-X7181	4.853 ms	1 - 1 MB	NPU
EfficientViT-b2-cls	QNN_DLC	float	Qualcomm® Dragonwing™ Q-8750	2.368 ms	1 - 70 MB	NPU
EfficientViT-b2-cls	QNN_DLC	float	Qualcomm® SA8295P	5.928 ms	0 - 71 MB	NPU
EfficientViT-b2-cls	QNN_DLC	w8a16	Snapdragon® 8 Elite Gen 5 For Galaxy Mobile	2.098 ms	0 - 113 MB	NPU
EfficientViT-b2-cls	QNN_DLC	w8a16	Snapdragon® 8 Elite For Galaxy Mobile	2.445 ms	0 - 111 MB	NPU
EfficientViT-b2-cls	QNN_DLC	w8a16	Snapdragon® X2 Elite	2.572 ms	0 - 0 MB	NPU
EfficientViT-b2-cls	QNN_DLC	w8a16	Snapdragon® X Elite	5.471 ms	0 - 0 MB	NPU
EfficientViT-b2-cls	QNN_DLC	w8a16	Snapdragon® 8 Gen 3 Mobile	3.361 ms	0 - 153 MB	NPU
EfficientViT-b2-cls	QNN_DLC	w8a16	Qualcomm® Dragonwing™ IQ-8275	4.503 ms	0 - 4 MB	NPU
EfficientViT-b2-cls	QNN_DLC	w8a16	Qualcomm® Dragonwing™ QCS8550 (Proxy)	5.051 ms	0 - 2 MB	NPU
EfficientViT-b2-cls	QNN_DLC	w8a16	Qualcomm® SA8650P	5.456 ms	0 - 106 MB	NPU
EfficientViT-b2-cls	QNN_DLC	w8a16	Qualcomm® SA8255P	5.456 ms	0 - 106 MB	NPU
EfficientViT-b2-cls	QNN_DLC	w8a16	Qualcomm® Dragonwing™ IQ-9075	5.337 ms	0 - 3 MB	NPU
EfficientViT-b2-cls	QNN_DLC	w8a16	Qualcomm® Dragonwing™ IQ-X7181	5.471 ms	0 - 0 MB	NPU
EfficientViT-b2-cls	QNN_DLC	w8a16	Qualcomm® Dragonwing™ Q-6690	24.119 ms	0 - 225 MB	NPU
EfficientViT-b2-cls	QNN_DLC	w8a16	Qualcomm® Dragonwing™ Q-7790	5.326 ms	0 - 218 MB	NPU
EfficientViT-b2-cls	QNN_DLC	w8a16	Qualcomm® Dragonwing™ Q-8750	2.445 ms	0 - 111 MB	NPU
EfficientViT-b2-cls	QNN_DLC	w8a16	Snapdragon® 7 Gen 4 Mobile	5.326 ms	0 - 218 MB	NPU
EfficientViT-b2-cls	TFLITE	float	Snapdragon® 8 Elite Gen 5 For Galaxy Mobile	2.07 ms	0 - 115 MB	NPU
EfficientViT-b2-cls	TFLITE	float	Snapdragon® 8 Elite For Galaxy Mobile	2.351 ms	0 - 109 MB	NPU
EfficientViT-b2-cls	TFLITE	float	Snapdragon® 8 Gen 3 Mobile	2.946 ms	0 - 179 MB	NPU
EfficientViT-b2-cls	TFLITE	float	Snapdragon® 8 Gen 1 Mobile	5.802 ms	0 - 181 MB	NPU
EfficientViT-b2-cls	TFLITE	float	Qualcomm® Dragonwing™ IQ-8275	4.652 ms	0 - 53 MB	NPU
EfficientViT-b2-cls	TFLITE	float	Qualcomm® Dragonwing™ QCS8550 (Proxy)	4.505 ms	0 - 7 MB	NPU
EfficientViT-b2-cls	TFLITE	float	Qualcomm® SA8650P	6.819 ms	0 - 111 MB	NPU
EfficientViT-b2-cls	TFLITE	float	Qualcomm® SA8255P	6.819 ms	0 - 111 MB	NPU
EfficientViT-b2-cls	TFLITE	float	Qualcomm® QCS8450	5.802 ms	0 - 181 MB	NPU
EfficientViT-b2-cls	TFLITE	float	Qualcomm® Dragonwing™ IQ-9075	5.117 ms	0 - 52 MB	NPU
EfficientViT-b2-cls	TFLITE	float	Qualcomm® Dragonwing™ Q-8750	2.351 ms	0 - 109 MB	NPU
EfficientViT-b2-cls	TFLITE	float	Qualcomm® SA8295P	5.924 ms	0 - 108 MB	NPU

License

The license for the original implementation of EfficientViT-b2-cls can be found here.

References

Community

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Paper for qualcomm/EfficientViT-b2-cls

EfficientViT: Lightweight Multi-Scale Attention for On-Device Semantic Segmentation

Paper • 2205.14756 • Published May 29, 2022 • 1