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

---

![](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/gpunet/web-assets/model_demo.png)

# GPUNet: Optimized for Qualcomm Devices

GPUNet 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 GPUNet found [here](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Classification/GPUNet).
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/main/src/qai_hub_models/models/gpunet) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).

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.

## 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](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/gpunet/releases/v0.51.0/gpunet-onnx-float.zip)
| ONNX | w8a16 | Universal | QAIRT 2.42, ONNX Runtime 1.24.3 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/gpunet/releases/v0.51.0/gpunet-onnx-w8a16.zip)
| ONNX | w8a8 | Universal | QAIRT 2.42, ONNX Runtime 1.24.3 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/gpunet/releases/v0.51.0/gpunet-onnx-w8a8.zip)
| QNN_DLC | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/gpunet/releases/v0.51.0/gpunet-qnn_dlc-float.zip)
| QNN_DLC | w8a16 | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/gpunet/releases/v0.51.0/gpunet-qnn_dlc-w8a16.zip)
| QNN_DLC | w8a8 | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/gpunet/releases/v0.51.0/gpunet-qnn_dlc-w8a8.zip)
| TFLITE | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/gpunet/releases/v0.51.0/gpunet-tflite-float.zip)
| TFLITE | w8a8 | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/gpunet/releases/v0.51.0/gpunet-tflite-w8a8.zip)

For more device-specific assets and performance metrics, visit **[GPUNet on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/gpunet)**.


### Option 2: Export with Custom Configurations

Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/main/src/qai_hub_models/models/gpunet) 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 [GPUNet on GitHub](https://github.com/qualcomm/ai-hub-models/blob/main/src/qai_hub_models/models/gpunet) for usage instructions.

## Model Details

**Model Type:** Model_use_case.image_classification

**Model Stats:**
- Model checkpoint: Imagenet
- Input resolution: 224x224
- Number of parameters: 10.49M
- Model size (float): 45.28MB
- Model size (w8a8): 21.3MB

## Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
|---|---|---|---|---|---|---
| GPUNet | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.507 ms | 0 - 36 MB | NPU
| GPUNet | ONNX | float | Snapdragon® X2 Elite | 0.463 ms | 24 - 24 MB | NPU
| GPUNet | ONNX | float | Snapdragon® X Elite | 1.121 ms | 24 - 24 MB | NPU
| GPUNet | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 0.782 ms | 0 - 59 MB | NPU
| GPUNet | ONNX | float | Qualcomm® QCS8550 (Proxy) | 1.043 ms | 0 - 2 MB | NPU
| GPUNet | ONNX | float | Qualcomm® QCS9075 | 1.357 ms | 1 - 3 MB | NPU
| GPUNet | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 0.6 ms | 0 - 30 MB | NPU
| GPUNet | ONNX | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 0.359 ms | 0 - 49 MB | NPU
| GPUNet | ONNX | w8a16 | Snapdragon® X2 Elite | 0.385 ms | 12 - 12 MB | NPU
| GPUNet | ONNX | w8a16 | Snapdragon® X Elite | 0.988 ms | 12 - 12 MB | NPU
| GPUNet | ONNX | w8a16 | Snapdragon® 8 Gen 3 Mobile | 0.58 ms | 0 - 64 MB | NPU
| GPUNet | ONNX | w8a16 | Qualcomm® QCS6490 | 98.781 ms | 22 - 31 MB | CPU
| GPUNet | ONNX | w8a16 | Qualcomm® QCS8550 (Proxy) | 0.826 ms | 0 - 2 MB | NPU
| GPUNet | ONNX | w8a16 | Qualcomm® QCS9075 | 0.985 ms | 0 - 3 MB | NPU
| GPUNet | ONNX | w8a16 | Qualcomm® QCM6690 | 49.699 ms | 30 - 38 MB | CPU
| GPUNet | ONNX | w8a16 | Snapdragon® 8 Elite For Galaxy Mobile | 0.431 ms | 0 - 44 MB | NPU
| GPUNet | ONNX | w8a16 | Snapdragon® 7 Gen 4 Mobile | 38.163 ms | 30 - 38 MB | CPU
| GPUNet | ONNX | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.351 ms | 0 - 48 MB | NPU
| GPUNet | ONNX | w8a8 | Snapdragon® X2 Elite | 0.311 ms | 12 - 12 MB | NPU
| GPUNet | ONNX | w8a8 | Snapdragon® X Elite | 0.744 ms | 12 - 12 MB | NPU
| GPUNet | ONNX | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.47 ms | 0 - 62 MB | NPU
| GPUNet | ONNX | w8a8 | Qualcomm® QCS6490 | 16.703 ms | 1 - 13 MB | CPU
| GPUNet | ONNX | w8a8 | Qualcomm® QCS8550 (Proxy) | 0.618 ms | 0 - 14 MB | NPU
| GPUNet | ONNX | w8a8 | Qualcomm® QCS9075 | 0.726 ms | 0 - 3 MB | NPU
| GPUNet | ONNX | w8a8 | Qualcomm® QCM6690 | 10.166 ms | 6 - 14 MB | CPU
| GPUNet | ONNX | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 0.394 ms | 0 - 38 MB | NPU
| GPUNet | ONNX | w8a8 | Snapdragon® 7 Gen 4 Mobile | 7.657 ms | 6 - 15 MB | CPU
| GPUNet | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.563 ms | 1 - 35 MB | NPU
| GPUNet | QNN_DLC | float | Snapdragon® X2 Elite | 0.654 ms | 1 - 1 MB | NPU
| GPUNet | QNN_DLC | float | Snapdragon® X Elite | 1.392 ms | 1 - 1 MB | NPU
| GPUNet | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 0.918 ms | 0 - 57 MB | NPU
| GPUNet | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 4.704 ms | 1 - 31 MB | NPU
| GPUNet | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 1.271 ms | 1 - 2 MB | NPU
| GPUNet | QNN_DLC | float | Qualcomm® SA8775P | 1.7 ms | 1 - 35 MB | NPU
| GPUNet | QNN_DLC | float | Qualcomm® QCS9075 | 1.589 ms | 3 - 5 MB | NPU
| GPUNet | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 2.415 ms | 0 - 62 MB | NPU
| GPUNet | QNN_DLC | float | Qualcomm® SA7255P | 4.704 ms | 1 - 31 MB | NPU
| GPUNet | QNN_DLC | float | Qualcomm® SA8295P | 2.267 ms | 0 - 31 MB | NPU
| GPUNet | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 0.704 ms | 0 - 30 MB | NPU
| GPUNet | QNN_DLC | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 0.434 ms | 0 - 44 MB | NPU
| GPUNet | QNN_DLC | w8a16 | Snapdragon® X2 Elite | 0.575 ms | 0 - 0 MB | NPU
| GPUNet | QNN_DLC | w8a16 | Snapdragon® X Elite | 1.245 ms | 0 - 0 MB | NPU
| GPUNet | QNN_DLC | w8a16 | Snapdragon® 8 Gen 3 Mobile | 0.77 ms | 0 - 58 MB | NPU
| GPUNet | QNN_DLC | w8a16 | Qualcomm® QCS6490 | 3.221 ms | 0 - 2 MB | NPU
| GPUNet | QNN_DLC | w8a16 | Qualcomm® QCS8275 (Proxy) | 2.473 ms | 0 - 41 MB | NPU
| GPUNet | QNN_DLC | w8a16 | Qualcomm® QCS8550 (Proxy) | 1.067 ms | 0 - 2 MB | NPU
| GPUNet | QNN_DLC | w8a16 | Qualcomm® SA8775P | 1.269 ms | 0 - 44 MB | NPU
| GPUNet | QNN_DLC | w8a16 | Qualcomm® QCS9075 | 1.231 ms | 2 - 4 MB | NPU
| GPUNet | QNN_DLC | w8a16 | Qualcomm® QCM6690 | 6.525 ms | 0 - 163 MB | NPU
| GPUNet | QNN_DLC | w8a16 | Qualcomm® QCS8450 (Proxy) | 1.451 ms | 0 - 61 MB | NPU
| GPUNet | QNN_DLC | w8a16 | Qualcomm® SA7255P | 2.473 ms | 0 - 41 MB | NPU
| GPUNet | QNN_DLC | w8a16 | Qualcomm® SA8295P | 1.688 ms | 0 - 39 MB | NPU
| GPUNet | QNN_DLC | w8a16 | Snapdragon® 8 Elite For Galaxy Mobile | 0.527 ms | 0 - 41 MB | NPU
| GPUNet | QNN_DLC | w8a16 | Snapdragon® 7 Gen 4 Mobile | 1.289 ms | 0 - 42 MB | NPU
| GPUNet | QNN_DLC | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.288 ms | 0 - 44 MB | NPU
| GPUNet | QNN_DLC | w8a8 | Snapdragon® X2 Elite | 0.352 ms | 0 - 0 MB | NPU
| GPUNet | QNN_DLC | w8a8 | Snapdragon® X Elite | 0.721 ms | 0 - 0 MB | NPU
| GPUNet | QNN_DLC | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.461 ms | 0 - 55 MB | NPU
| GPUNet | QNN_DLC | w8a8 | Qualcomm® QCS6490 | 2.004 ms | 0 - 2 MB | NPU
| GPUNet | QNN_DLC | w8a8 | Qualcomm® QCS8275 (Proxy) | 1.41 ms | 0 - 39 MB | NPU
| GPUNet | QNN_DLC | w8a8 | Qualcomm® QCS8550 (Proxy) | 0.612 ms | 0 - 1 MB | NPU
| GPUNet | QNN_DLC | w8a8 | Qualcomm® SA8775P | 0.799 ms | 0 - 40 MB | NPU
| GPUNet | QNN_DLC | w8a8 | Qualcomm® QCS9075 | 0.688 ms | 2 - 4 MB | NPU
| GPUNet | QNN_DLC | w8a8 | Qualcomm® QCM6690 | 3.454 ms | 0 - 42 MB | NPU
| GPUNet | QNN_DLC | w8a8 | Qualcomm® QCS8450 (Proxy) | 0.854 ms | 0 - 57 MB | NPU
| GPUNet | QNN_DLC | w8a8 | Qualcomm® SA7255P | 1.41 ms | 0 - 39 MB | NPU
| GPUNet | QNN_DLC | w8a8 | Qualcomm® SA8295P | 1.126 ms | 0 - 37 MB | NPU
| GPUNet | QNN_DLC | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 0.346 ms | 0 - 37 MB | NPU
| GPUNet | QNN_DLC | w8a8 | Snapdragon® 7 Gen 4 Mobile | 0.784 ms | 0 - 40 MB | NPU
| GPUNet | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.558 ms | 0 - 47 MB | NPU
| GPUNet | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 0.904 ms | 0 - 74 MB | NPU
| GPUNet | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 4.708 ms | 0 - 44 MB | NPU
| GPUNet | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 1.266 ms | 0 - 2 MB | NPU
| GPUNet | TFLITE | float | Qualcomm® SA8775P | 1.757 ms | 0 - 45 MB | NPU
| GPUNet | TFLITE | float | Qualcomm® QCS9075 | 1.579 ms | 0 - 27 MB | NPU
| GPUNet | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 2.402 ms | 0 - 79 MB | NPU
| GPUNet | TFLITE | float | Qualcomm® SA7255P | 4.708 ms | 0 - 44 MB | NPU
| GPUNet | TFLITE | float | Qualcomm® SA8295P | 2.278 ms | 0 - 44 MB | NPU
| GPUNet | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 0.71 ms | 0 - 47 MB | NPU
| GPUNet | TFLITE | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.239 ms | 0 - 45 MB | NPU
| GPUNet | TFLITE | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.33 ms | 0 - 56 MB | NPU
| GPUNet | TFLITE | w8a8 | Qualcomm® QCS6490 | 1.599 ms | 0 - 15 MB | NPU
| GPUNet | TFLITE | w8a8 | Qualcomm® QCS8275 (Proxy) | 1.121 ms | 0 - 39 MB | NPU
| GPUNet | TFLITE | w8a8 | Qualcomm® QCS8550 (Proxy) | 0.429 ms | 0 - 10 MB | NPU
| GPUNet | TFLITE | w8a8 | Qualcomm® SA8775P | 0.637 ms | 0 - 42 MB | NPU
| GPUNet | TFLITE | w8a8 | Qualcomm® QCS9075 | 0.525 ms | 0 - 14 MB | NPU
| GPUNet | TFLITE | w8a8 | Qualcomm® QCM6690 | 3.033 ms | 0 - 40 MB | NPU
| GPUNet | TFLITE | w8a8 | Qualcomm® QCS8450 (Proxy) | 0.684 ms | 0 - 58 MB | NPU
| GPUNet | TFLITE | w8a8 | Qualcomm® SA7255P | 1.121 ms | 0 - 39 MB | NPU
| GPUNet | TFLITE | w8a8 | Qualcomm® SA8295P | 0.903 ms | 0 - 37 MB | NPU
| GPUNet | TFLITE | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 0.274 ms | 0 - 38 MB | NPU
| GPUNet | TFLITE | w8a8 | Snapdragon® 7 Gen 4 Mobile | 0.617 ms | 0 - 38 MB | NPU

## License
* The license for the original implementation of GPUNet can be found
  [here](http://www.apache.org/licenses/LICENSE-2.0).

## References
* [GPUNet: Searching the Deployable Convolution Neural Networks for GPUs](https://arxiv.org/abs/2205.00841)
* [Source Model Implementation](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Classification/GPUNet)

## Community
* Join [our AI Hub Slack community](https://aihub.qualcomm.com/community/slack) to collaborate, post questions and learn more about on-device AI.
* For questions or feedback please [reach out to us](mailto:ai-hub-support@qti.qualcomm.com).