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metadata 
library_name: pytorch
license: other
tags:
  - backbone
  - bu_auto
  - android
pipeline_tag: image-classification

EfficientNet-V2-s: Optimized for Qualcomm Devices

EfficientNetV2-s 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 EfficientNet-V2-s 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 w8a16 Universal QAIRT 2.37, ONNX Runtime 1.23.0 Download
QNN_DLC float Universal QAIRT 2.42 Download
QNN_DLC w8a16 Universal QAIRT 2.42 Download
TFLITE float Universal QAIRT 2.42, TFLite 2.17.0 Download

For more device-specific assets and performance metrics, visit EfficientNet-V2-s 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 EfficientNet-V2-s on GitHub for usage instructions.

Model Details

Model Type: Model_use_case.image_classification

Model Stats:

  • Model checkpoint: Imagenet
  • Input resolution: 384x384
  • Number of parameters: 21.4M
  • Model size (float): 81.7 MB
  • Model size (w8a16): 27.2 MB

Performance Summary

Model Runtime Precision Chipset Inference Time (ms) Peak Memory Range (MB) Primary Compute Unit
EfficientNet-V2-s ONNX float Snapdragon® X Elite 2.668 ms 47 - 47 MB NPU
EfficientNet-V2-s ONNX float Snapdragon® 8 Gen 3 Mobile 2.012 ms 0 - 211 MB NPU
EfficientNet-V2-s ONNX float Qualcomm® QCS8550 (Proxy) 2.716 ms 0 - 134 MB NPU
EfficientNet-V2-s ONNX float Qualcomm® QCS9075 3.615 ms 0 - 4 MB NPU
EfficientNet-V2-s ONNX float Snapdragon® 8 Elite For Galaxy Mobile 1.591 ms 0 - 134 MB NPU
EfficientNet-V2-s ONNX float Snapdragon® 8 Elite Gen 5 Mobile 1.358 ms 0 - 134 MB NPU
EfficientNet-V2-s ONNX w8a16 Snapdragon® X Elite 2.631 ms 24 - 24 MB NPU
EfficientNet-V2-s ONNX w8a16 Snapdragon® 8 Gen 3 Mobile 1.826 ms 0 - 228 MB NPU
EfficientNet-V2-s ONNX w8a16 Qualcomm® QCS6490 311.643 ms 25 - 32 MB CPU
EfficientNet-V2-s ONNX w8a16 Qualcomm® QCS8550 (Proxy) 2.624 ms 0 - 31 MB NPU
EfficientNet-V2-s ONNX w8a16 Qualcomm® QCS9075 2.989 ms 0 - 3 MB NPU
EfficientNet-V2-s ONNX w8a16 Qualcomm® QCM6690 142.621 ms 13 - 26 MB CPU
EfficientNet-V2-s ONNX w8a16 Snapdragon® 8 Elite For Galaxy Mobile 1.335 ms 0 - 183 MB NPU
EfficientNet-V2-s ONNX w8a16 Snapdragon® 7 Gen 4 Mobile 130.814 ms 15 - 28 MB CPU
EfficientNet-V2-s ONNX w8a16 Snapdragon® 8 Elite Gen 5 Mobile 1.121 ms 0 - 183 MB NPU
EfficientNet-V2-s QNN_DLC float Snapdragon® X Elite 2.943 ms 1 - 1 MB NPU
EfficientNet-V2-s QNN_DLC float Snapdragon® 8 Gen 3 Mobile 1.959 ms 0 - 145 MB NPU
EfficientNet-V2-s QNN_DLC float Qualcomm® QCS8275 (Proxy) 10.921 ms 1 - 66 MB NPU
EfficientNet-V2-s QNN_DLC float Qualcomm® QCS8550 (Proxy) 2.671 ms 1 - 2 MB NPU
EfficientNet-V2-s QNN_DLC float Qualcomm® QCS9075 3.659 ms 1 - 3 MB NPU
EfficientNet-V2-s QNN_DLC float Qualcomm® QCS8450 (Proxy) 5.634 ms 0 - 155 MB NPU
EfficientNet-V2-s QNN_DLC float Snapdragon® 8 Elite For Galaxy Mobile 1.549 ms 0 - 68 MB NPU
EfficientNet-V2-s QNN_DLC float Snapdragon® 8 Elite Gen 5 Mobile 1.218 ms 0 - 69 MB NPU
EfficientNet-V2-s QNN_DLC w8a16 Snapdragon® X Elite 2.929 ms 0 - 0 MB NPU
EfficientNet-V2-s QNN_DLC w8a16 Snapdragon® 8 Gen 3 Mobile 1.775 ms 0 - 147 MB NPU
EfficientNet-V2-s QNN_DLC w8a16 Qualcomm® QCS6490 6.816 ms 0 - 2 MB NPU
EfficientNet-V2-s QNN_DLC w8a16 Qualcomm® QCS8275 (Proxy) 5.339 ms 0 - 105 MB NPU
EfficientNet-V2-s QNN_DLC w8a16 Qualcomm® QCS8550 (Proxy) 2.61 ms 0 - 2 MB NPU
EfficientNet-V2-s QNN_DLC w8a16 Qualcomm® QCS9075 2.937 ms 0 - 2 MB NPU
EfficientNet-V2-s QNN_DLC w8a16 Qualcomm® QCM6690 14.296 ms 0 - 226 MB NPU
EfficientNet-V2-s QNN_DLC w8a16 Qualcomm® QCS8450 (Proxy) 3.23 ms 0 - 153 MB NPU
EfficientNet-V2-s QNN_DLC w8a16 Snapdragon® 8 Elite For Galaxy Mobile 1.235 ms 0 - 108 MB NPU
EfficientNet-V2-s QNN_DLC w8a16 Snapdragon® 7 Gen 4 Mobile 2.919 ms 0 - 105 MB NPU
EfficientNet-V2-s QNN_DLC w8a16 Snapdragon® 8 Elite Gen 5 Mobile 1.001 ms 0 - 109 MB NPU
EfficientNet-V2-s TFLITE float Snapdragon® 8 Gen 3 Mobile 1.952 ms 0 - 196 MB NPU
EfficientNet-V2-s TFLITE float Qualcomm® QCS8275 (Proxy) 10.991 ms 0 - 113 MB NPU
EfficientNet-V2-s TFLITE float Qualcomm® QCS8550 (Proxy) 2.632 ms 0 - 2 MB NPU
EfficientNet-V2-s TFLITE float Qualcomm® QCS9075 3.673 ms 0 - 50 MB NPU
EfficientNet-V2-s TFLITE float Qualcomm® QCS8450 (Proxy) 5.714 ms 0 - 205 MB NPU
EfficientNet-V2-s TFLITE float Snapdragon® 8 Elite For Galaxy Mobile 1.504 ms 0 - 120 MB NPU
EfficientNet-V2-s TFLITE float Snapdragon® 8 Elite Gen 5 Mobile 1.226 ms 0 - 117 MB NPU

License

  • The license for the original implementation of EfficientNet-V2-s can be found here.

References

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