v0.59.0
Browse filesSee https://github.com/qualcomm/ai-hub-models/releases/v0.59.0 for changelog.
- README.md +82 -85
- release_assets.json +18 -19
README.md
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@@ -16,7 +16,7 @@ pipeline_tag: image-classification
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EfficientNetB4 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.
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This is based on the implementation of EfficientNet-B4 found [here](https://github.com/pytorch/vision/blob/main/torchvision/models/efficientnet.py).
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This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.
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Qualcomm AI Hub Models uses [Qualcomm AI Hub Workbench](https://workbench.aihub.qualcomm.com) to compile, profile, and evaluate this model. [Sign up](https://myaccount.qualcomm.com/signup) to run these models on a hosted Qualcomm® device.
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| Runtime | Precision | Chipset | SDK Versions | Download |
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|---|---|---|---|---|
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| ONNX | float | Universal | QAIRT 2.45, ONNX Runtime 1.
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| ONNX | w8a16 | Universal | QAIRT 2.45, ONNX Runtime 1.
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| QNN_DLC | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_b4/releases/v0.
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| QNN_DLC | w8a16 | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_b4/releases/v0.
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| TFLITE | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_b4/releases/v0.
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For more device-specific assets and performance metrics, visit **[EfficientNet-B4 on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/efficientnet_b4)**.
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### Option 2: Export with Custom Configurations
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Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.
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- Custom weights (e.g., fine-tuned checkpoints)
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- Custom input shapes
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- Target device and runtime configurations
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This option is ideal if you need to customize the model beyond the default configuration provided here.
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See our repository for [EfficientNet-B4 on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.
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## Model Details
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| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
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|---|---|---|---|---|---|---
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| EfficientNet-B4 | ONNX | float | Snapdragon® X2 Elite | 3.918 ms | 2 - 2 MB | NPU
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| EfficientNet-B4 | ONNX | float | Snapdragon® X Elite | 7.
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| EfficientNet-B4 | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 5.
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| EfficientNet-B4 | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 20.
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| EfficientNet-B4 | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 7.
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| EfficientNet-B4 | ONNX | float | Qualcomm® QCS8450 | 20.
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| EfficientNet-B4 | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 9.
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| EfficientNet-B4 | ONNX | float |
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| EfficientNet-B4 | ONNX | float |
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| EfficientNet-B4 | ONNX | float |
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| EfficientNet-B4 | ONNX | float |
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| EfficientNet-B4 | ONNX | w8a16 | Snapdragon® X2 Elite | 2.
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| EfficientNet-B4 | ONNX | w8a16 | Snapdragon® X Elite | 8.
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| EfficientNet-B4 | ONNX | w8a16 | Snapdragon® 8 Gen 3 Mobile | 5.
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| EfficientNet-B4 | ONNX | w8a16 | Snapdragon® 8 Gen 1 Mobile | 8.
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| EfficientNet-B4 | ONNX | w8a16 | Qualcomm® Dragonwing™ QCS6490 |
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| EfficientNet-B4 | ONNX | w8a16 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 7.
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| EfficientNet-B4 | ONNX | w8a16 | Qualcomm® QCS8450 | 8.
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| EfficientNet-B4 | ONNX | w8a16 | Qualcomm® Dragonwing™ IQ-9075 | 7.
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| EfficientNet-B4 | ONNX | w8a16 |
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| EfficientNet-B4 | ONNX | w8a16 |
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| EfficientNet-B4 | ONNX | w8a16 |
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| EfficientNet-B4 | ONNX | w8a16 | Snapdragon® 8 Elite Mobile |
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| EfficientNet-B4 |
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| EfficientNet-B4 |
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| EfficientNet-B4 |
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| EfficientNet-B4 | QNN_DLC | float | Snapdragon®
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| EfficientNet-B4 | QNN_DLC | float |
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| EfficientNet-B4 | QNN_DLC | float |
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| EfficientNet-B4 | QNN_DLC | float |
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| EfficientNet-B4 | QNN_DLC | float | Qualcomm®
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| EfficientNet-B4 | QNN_DLC | float | Qualcomm®
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| EfficientNet-B4 | QNN_DLC | float | Qualcomm®
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| EfficientNet-B4 | QNN_DLC | float | Qualcomm®
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| EfficientNet-B4 | QNN_DLC | float | Qualcomm®
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| EfficientNet-B4 | QNN_DLC | float | Qualcomm®
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| EfficientNet-B4 | QNN_DLC | float | Qualcomm®
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| EfficientNet-B4 | QNN_DLC | float |
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| EfficientNet-B4 | QNN_DLC | float |
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| EfficientNet-B4 | QNN_DLC | float | Snapdragon® 8 Elite Mobile |
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| EfficientNet-B4 | QNN_DLC |
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| EfficientNet-B4 | QNN_DLC |
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| EfficientNet-B4 | QNN_DLC |
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| EfficientNet-B4 | QNN_DLC | w8a16 | Snapdragon®
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| EfficientNet-B4 | QNN_DLC | w8a16 |
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| EfficientNet-B4 | QNN_DLC | w8a16 |
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| EfficientNet-B4 | QNN_DLC | w8a16 |
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| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm®
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| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm®
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| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm®
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| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm®
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| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm®
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| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm®
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| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm®
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| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® Dragonwing™
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| EfficientNet-B4 | QNN_DLC | w8a16 |
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| EfficientNet-B4 | QNN_DLC | w8a16 |
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| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm®
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| EfficientNet-B4 | QNN_DLC | w8a16 |
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| EfficientNet-B4 | QNN_DLC | w8a16 | Snapdragon® 8 Elite Mobile | 3.
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| EfficientNet-B4 | QNN_DLC | w8a16 |
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| EfficientNet-B4 |
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| EfficientNet-B4 |
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| EfficientNet-B4 |
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| EfficientNet-B4 | TFLITE | float |
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| EfficientNet-B4 | TFLITE | float |
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| EfficientNet-B4 | TFLITE | float | Qualcomm®
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| EfficientNet-B4 | TFLITE | float | Qualcomm®
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| EfficientNet-B4 | TFLITE | float | Qualcomm®
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| EfficientNet-B4 | TFLITE | float | Qualcomm®
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| EfficientNet-B4 | TFLITE | float | Qualcomm®
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| EfficientNet-B4 | TFLITE | float | Qualcomm®
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| EfficientNet-B4 | TFLITE | float | Qualcomm®
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| EfficientNet-B4 | TFLITE | float | Snapdragon® 8 Elite
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| EfficientNet-B4 | TFLITE | float |
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| EfficientNet-B4 | TFLITE | float | Snapdragon® 8 Elite Mobile | 4.313 ms | 0 - 105 MB | NPU
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| EfficientNet-B4 | TFLITE | float | Qualcomm® SA8295P | 18.842 ms | 0 - 140 MB | NPU
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| EfficientNet-B4 | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 4.313 ms | 0 - 105 MB | NPU
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## License
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* The license for the original implementation of EfficientNet-B4 can be found
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EfficientNetB4 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.
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This is based on the implementation of EfficientNet-B4 found [here](https://github.com/pytorch/vision/blob/main/torchvision/models/efficientnet.py).
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+
This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.59.0/src/qai_hub_models/models/efficientnet_b4) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).
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Qualcomm AI Hub Models uses [Qualcomm AI Hub Workbench](https://workbench.aihub.qualcomm.com) to compile, profile, and evaluate this model. [Sign up](https://myaccount.qualcomm.com/signup) to run these models on a hosted Qualcomm® device.
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| Runtime | Precision | Chipset | SDK Versions | Download |
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|---|---|---|---|---|
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| ONNX | float | Universal | QAIRT 2.45, ONNX Runtime 1.27.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_b4/releases/v0.59.0/efficientnet_b4-onnx-float.zip)
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| ONNX | w8a16 | Universal | QAIRT 2.45, ONNX Runtime 1.27.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_b4/releases/v0.59.0/efficientnet_b4-onnx-w8a16.zip)
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| QNN_DLC | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_b4/releases/v0.59.0/efficientnet_b4-qnn_dlc-float.zip)
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| QNN_DLC | w8a16 | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_b4/releases/v0.59.0/efficientnet_b4-qnn_dlc-w8a16.zip)
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| TFLITE | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/efficientnet_b4/releases/v0.59.0/efficientnet_b4-tflite-float.zip)
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For more device-specific assets and performance metrics, visit **[EfficientNet-B4 on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/efficientnet_b4)**.
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### Option 2: Export with Custom Configurations
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Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.59.0/src/qai_hub_models/models/efficientnet_b4) Python library to compile and export the model with your own:
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- Custom weights (e.g., fine-tuned checkpoints)
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- Custom input shapes
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- Target device and runtime configurations
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This option is ideal if you need to customize the model beyond the default configuration provided here.
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See our repository for [EfficientNet-B4 on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.59.0/src/qai_hub_models/models/efficientnet_b4) for usage instructions.
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## Model Details
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| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
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|---|---|---|---|---|---|---
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| EfficientNet-B4 | ONNX | float | Snapdragon® X2 Elite | 3.918 ms | 2 - 2 MB | NPU
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| EfficientNet-B4 | ONNX | float | Snapdragon® X Elite | 7.724 ms | 45 - 45 MB | NPU
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| EfficientNet-B4 | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 5.31 ms | 2 - 149 MB | NPU
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| EfficientNet-B4 | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 20.504 ms | 0 - 187 MB | NPU
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| EfficientNet-B4 | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 7.341 ms | 0 - 218 MB | NPU
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| EfficientNet-B4 | ONNX | float | Qualcomm® QCS8450 | 20.504 ms | 0 - 187 MB | NPU
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| EfficientNet-B4 | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 9.342 ms | 1 - 6 MB | NPU
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| EfficientNet-B4 | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 7.724 ms | 45 - 45 MB | NPU
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| EfficientNet-B4 | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 4.052 ms | 0 - 89 MB | NPU
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| EfficientNet-B4 | ONNX | float | Snapdragon® 8 Elite Mobile | 4.052 ms | 0 - 89 MB | NPU
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| EfficientNet-B4 | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 3.113 ms | 0 - 205 MB | NPU
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| EfficientNet-B4 | ONNX | w8a16 | Snapdragon® X2 Elite | 2.917 ms | 2 - 2 MB | NPU
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| EfficientNet-B4 | ONNX | w8a16 | Snapdragon® X Elite | 8.032 ms | 23 - 23 MB | NPU
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| EfficientNet-B4 | ONNX | w8a16 | Snapdragon® 8 Gen 3 Mobile | 5.079 ms | 1 - 226 MB | NPU
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| EfficientNet-B4 | ONNX | w8a16 | Snapdragon® 8 Gen 1 Mobile | 8.907 ms | 0 - 227 MB | NPU
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| EfficientNet-B4 | ONNX | w8a16 | Qualcomm® Dragonwing™ QCS6490 | 33.142 ms | 0 - 4 MB | NPU
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| EfficientNet-B4 | ONNX | w8a16 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 7.615 ms | 0 - 30 MB | NPU
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| EfficientNet-B4 | ONNX | w8a16 | Qualcomm® QCS8450 | 8.907 ms | 0 - 227 MB | NPU
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| EfficientNet-B4 | ONNX | w8a16 | Qualcomm® Dragonwing™ IQ-9075 | 7.96 ms | 1 - 4 MB | NPU
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| EfficientNet-B4 | ONNX | w8a16 | Qualcomm® Dragonwing™ IQ-X7181 | 8.032 ms | 23 - 23 MB | NPU
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| EfficientNet-B4 | ONNX | w8a16 | Qualcomm® Dragonwing™ Q-8750 | 3.413 ms | 0 - 170 MB | NPU
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| EfficientNet-B4 | ONNX | w8a16 | Snapdragon® 8 Elite Mobile | 3.413 ms | 0 - 170 MB | NPU
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| EfficientNet-B4 | ONNX | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 2.75 ms | 0 - 178 MB | NPU
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| EfficientNet-B4 | QNN_DLC | float | Snapdragon® X2 Elite | 4.558 ms | 2 - 2 MB | NPU
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| EfficientNet-B4 | QNN_DLC | float | Snapdragon® X Elite | 8.862 ms | 2 - 2 MB | NPU
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| EfficientNet-B4 | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 5.807 ms | 0 - 142 MB | NPU
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| EfficientNet-B4 | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 23.025 ms | 2 - 187 MB | NPU
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| EfficientNet-B4 | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8275 | 29.127 ms | 2 - 82 MB | NPU
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| EfficientNet-B4 | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 8.151 ms | 2 - 165 MB | NPU
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| EfficientNet-B4 | QNN_DLC | float | Qualcomm® SA8775P | 10.296 ms | 2 - 85 MB | NPU
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| EfficientNet-B4 | QNN_DLC | float | Qualcomm® SA8650P | 10.296 ms | 2 - 85 MB | NPU
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| EfficientNet-B4 | QNN_DLC | float | Qualcomm® SA8255P | 10.296 ms | 2 - 85 MB | NPU
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| EfficientNet-B4 | QNN_DLC | float | Qualcomm® QCS8450 | 23.025 ms | 2 - 187 MB | NPU
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| EfficientNet-B4 | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 10.032 ms | 4 - 7 MB | NPU
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| EfficientNet-B4 | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 8.862 ms | 2 - 2 MB | NPU
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| EfficientNet-B4 | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 4.302 ms | 2 - 89 MB | NPU
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| EfficientNet-B4 | QNN_DLC | float | Qualcomm® SA7255P | 29.127 ms | 2 - 82 MB | NPU
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| EfficientNet-B4 | QNN_DLC | float | Qualcomm® SA8295P | 18.782 ms | 2 - 123 MB | NPU
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| EfficientNet-B4 | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 4.302 ms | 2 - 89 MB | NPU
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| EfficientNet-B4 | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 3.356 ms | 2 - 208 MB | NPU
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| EfficientNet-B4 | QNN_DLC | w8a16 | Snapdragon® X2 Elite | 3.553 ms | 1 - 1 MB | NPU
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| EfficientNet-B4 | QNN_DLC | w8a16 | Snapdragon® X Elite | 9.1 ms | 1 - 1 MB | NPU
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| EfficientNet-B4 | QNN_DLC | w8a16 | Snapdragon® 8 Gen 3 Mobile | 5.63 ms | 1 - 197 MB | NPU
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| EfficientNet-B4 | QNN_DLC | w8a16 | Snapdragon® 8 Gen 1 Mobile | 11.375 ms | 1 - 201 MB | NPU
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| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ QCS6490 | 33.639 ms | 3 - 5 MB | NPU
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| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ QCS8275 | 15.405 ms | 1 - 141 MB | NPU
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| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 8.363 ms | 1 - 212 MB | NPU
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| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® SA8775P | 8.902 ms | 1 - 143 MB | NPU
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| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® SA8650P | 8.902 ms | 1 - 143 MB | NPU
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| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® SA8255P | 8.902 ms | 1 - 143 MB | NPU
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| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® QCS8450 | 11.375 ms | 1 - 201 MB | NPU
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| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-9075 | 8.648 ms | 1 - 3 MB | NPU
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| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-X7181 | 9.1 ms | 1 - 1 MB | NPU
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| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-6690 | 48.82 ms | 1 - 275 MB | NPU
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| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-7790 | 9.736 ms | 1 - 269 MB | NPU
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| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-8750 | 3.704 ms | 0 - 145 MB | NPU
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| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® SA7255P | 15.405 ms | 1 - 141 MB | NPU
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| EfficientNet-B4 | QNN_DLC | w8a16 | Qualcomm® SA8295P | 10.916 ms | 1 - 143 MB | NPU
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| EfficientNet-B4 | QNN_DLC | w8a16 | Snapdragon® 8 Elite Mobile | 3.704 ms | 0 - 145 MB | NPU
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| 125 |
+
| EfficientNet-B4 | QNN_DLC | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 3.012 ms | 1 - 156 MB | NPU
|
| 126 |
+
| EfficientNet-B4 | QNN_DLC | w8a16 | Snapdragon® 7 Gen 4 Mobile | 9.736 ms | 1 - 269 MB | NPU
|
| 127 |
+
| EfficientNet-B4 | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 5.754 ms | 0 - 163 MB | NPU
|
| 128 |
+
| EfficientNet-B4 | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 21.764 ms | 0 - 203 MB | NPU
|
| 129 |
+
| EfficientNet-B4 | TFLITE | float | Qualcomm® Dragonwing™ QCS8275 | 28.922 ms | 0 - 97 MB | NPU
|
| 130 |
+
| EfficientNet-B4 | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 8.016 ms | 0 - 2 MB | NPU
|
| 131 |
+
| EfficientNet-B4 | TFLITE | float | Qualcomm® SA8775P | 10.288 ms | 0 - 100 MB | NPU
|
| 132 |
+
| EfficientNet-B4 | TFLITE | float | Qualcomm® SA8650P | 10.288 ms | 0 - 100 MB | NPU
|
| 133 |
+
| EfficientNet-B4 | TFLITE | float | Qualcomm® SA8255P | 10.288 ms | 0 - 100 MB | NPU
|
| 134 |
+
| EfficientNet-B4 | TFLITE | float | Qualcomm® QCS8450 | 21.764 ms | 0 - 203 MB | NPU
|
| 135 |
+
| EfficientNet-B4 | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 9.989 ms | 0 - 49 MB | NPU
|
| 136 |
+
| EfficientNet-B4 | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 4.317 ms | 0 - 104 MB | NPU
|
| 137 |
+
| EfficientNet-B4 | TFLITE | float | Qualcomm® SA7255P | 28.922 ms | 0 - 97 MB | NPU
|
| 138 |
+
| EfficientNet-B4 | TFLITE | float | Qualcomm® SA8295P | 18.851 ms | 0 - 139 MB | NPU
|
| 139 |
+
| EfficientNet-B4 | TFLITE | float | Snapdragon® 8 Elite Mobile | 4.317 ms | 0 - 104 MB | NPU
|
| 140 |
+
| EfficientNet-B4 | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 3.216 ms | 0 - 98 MB | NPU
|
|
|
|
|
|
|
|
|
|
| 141 |
|
| 142 |
## License
|
| 143 |
* The license for the original implementation of EfficientNet-B4 can be found
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"qnn_dlc": {
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| 8 |
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| 10 |
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| 11 |
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| 12 |
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| 13 |
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| 15 |
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| 16 |
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| 18 |
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| 19 |
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| 21 |
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| 35 |
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