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RegNet-Y-800MF

Image Classification
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android
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RegNet-Y-800MF
File size: 9,812 Bytes 
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---
library_name: pytorch
license: other
tags:
- android
pipeline_tag: image-classification

---

![](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/regnet_y_800mf/web-assets/model_demo.png)

# RegNet-Y-800MF: Optimized for Qualcomm Devices

RegNet_Y_800MF is part of the RegNet family of models designed for efficient and scalable image classification. It uses a simple yet effective design space to balance performance and computational cost, making it suitable for mobile and edge devices.

This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/regnet_y_800mf) 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 2.37, ONNX Runtime 1.23.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/regnet_y_800mf/releases/v0.46.0/regnet_y_800mf-onnx-float.zip)
| ONNX | w8a8 | Universal | QAIRT 2.37, ONNX Runtime 1.23.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/regnet_y_800mf/releases/v0.46.0/regnet_y_800mf-onnx-w8a8.zip)
| QNN_DLC | float | Universal | QAIRT 2.42 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/regnet_y_800mf/releases/v0.46.0/regnet_y_800mf-qnn_dlc-float.zip)
| QNN_DLC | w8a8 | Universal | QAIRT 2.42 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/regnet_y_800mf/releases/v0.46.0/regnet_y_800mf-qnn_dlc-w8a8.zip)
| TFLITE | float | Universal | QAIRT 2.42, TFLite 2.17.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/regnet_y_800mf/releases/v0.46.0/regnet_y_800mf-tflite-float.zip)
| TFLITE | w8a8 | Universal | QAIRT 2.42, TFLite 2.17.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/regnet_y_800mf/releases/v0.46.0/regnet_y_800mf-tflite-w8a8.zip)

For more device-specific assets and performance metrics, visit **[RegNet-Y-800MF on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/regnet_y_800mf)**.


### Option 2: Export with Custom Configurations

Use the [Qualcomm® AI Hub Models](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/regnet_y_800mf) 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 [RegNet-Y-800MF on GitHub](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/regnet_y_800mf) for usage instructions.

## Model Details

**Model Type:** Model_use_case.image_classification

**Model Stats:**
- Model checkpoint: regnet_y_800mf-1b27b58c.pth
- Input resolution: 1x3x224
- Model size: ~6.3 MB

## Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
|---|---|---|---|---|---|---
| RegNet-Y-800MF | ONNX | float | Snapdragon® X Elite | 1.28 ms | 14 - 14 MB | NPU
| RegNet-Y-800MF | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 0.92 ms | 0 - 141 MB | NPU
| RegNet-Y-800MF | ONNX | float | Qualcomm® QCS8550 (Proxy) | 1.316 ms | 0 - 23 MB | NPU
| RegNet-Y-800MF | ONNX | float | Qualcomm® QCS9075 | 1.711 ms | 1 - 3 MB | NPU
| RegNet-Y-800MF | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 0.718 ms | 0 - 119 MB | NPU
| RegNet-Y-800MF | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.691 ms | 0 - 119 MB | NPU
| RegNet-Y-800MF | ONNX | w8a8 | Snapdragon® X Elite | 0.86 ms | 7 - 7 MB | NPU
| RegNet-Y-800MF | ONNX | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.688 ms | 0 - 145 MB | NPU
| RegNet-Y-800MF | ONNX | w8a8 | Qualcomm® QCS6490 | 15.069 ms | 4 - 12 MB | CPU
| RegNet-Y-800MF | ONNX | w8a8 | Qualcomm® QCS8550 (Proxy) | 0.93 ms | 0 - 114 MB | NPU
| RegNet-Y-800MF | ONNX | w8a8 | Qualcomm® QCS9075 | 1.101 ms | 0 - 3 MB | NPU
| RegNet-Y-800MF | ONNX | w8a8 | Qualcomm® QCM6690 | 8.409 ms | 5 - 15 MB | CPU
| RegNet-Y-800MF | ONNX | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 0.579 ms | 0 - 122 MB | NPU
| RegNet-Y-800MF | ONNX | w8a8 | Snapdragon® 7 Gen 4 Mobile | 6.27 ms | 6 - 15 MB | CPU
| RegNet-Y-800MF | ONNX | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.524 ms | 0 - 123 MB | NPU
| RegNet-Y-800MF | QNN_DLC | float | Snapdragon® X Elite | 1.638 ms | 1 - 1 MB | NPU
| RegNet-Y-800MF | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 0.915 ms | 0 - 78 MB | NPU
| RegNet-Y-800MF | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 4.019 ms | 1 - 53 MB | NPU
| RegNet-Y-800MF | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 1.381 ms | 1 - 2 MB | NPU
| RegNet-Y-800MF | QNN_DLC | float | Qualcomm® SA8775P | 1.878 ms | 1 - 56 MB | NPU
| RegNet-Y-800MF | QNN_DLC | float | Qualcomm® QCS9075 | 1.716 ms | 1 - 3 MB | NPU
| RegNet-Y-800MF | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 2.22 ms | 0 - 72 MB | NPU
| RegNet-Y-800MF | QNN_DLC | float | Qualcomm® SA7255P | 4.019 ms | 1 - 53 MB | NPU
| RegNet-Y-800MF | QNN_DLC | float | Qualcomm® SA8295P | 2.183 ms | 0 - 48 MB | NPU
| RegNet-Y-800MF | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 0.69 ms | 0 - 58 MB | NPU
| RegNet-Y-800MF | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.605 ms | 1 - 57 MB | NPU
| RegNet-Y-800MF | QNN_DLC | w8a8 | Snapdragon® X Elite | 0.869 ms | 0 - 0 MB | NPU
| RegNet-Y-800MF | QNN_DLC | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.492 ms | 0 - 65 MB | NPU
| RegNet-Y-800MF | QNN_DLC | w8a8 | Qualcomm® QCS6490 | 1.708 ms | 0 - 2 MB | NPU
| RegNet-Y-800MF | QNN_DLC | w8a8 | Qualcomm® QCS8275 (Proxy) | 1.618 ms | 0 - 46 MB | NPU
| RegNet-Y-800MF | QNN_DLC | w8a8 | Qualcomm® QCS8550 (Proxy) | 0.689 ms | 0 - 2 MB | NPU
| RegNet-Y-800MF | QNN_DLC | w8a8 | Qualcomm® SA8775P | 3.777 ms | 0 - 46 MB | NPU
| RegNet-Y-800MF | QNN_DLC | w8a8 | Qualcomm® QCS9075 | 0.85 ms | 0 - 2 MB | NPU
| RegNet-Y-800MF | QNN_DLC | w8a8 | Qualcomm® QCM6690 | 2.802 ms | 0 - 47 MB | NPU
| RegNet-Y-800MF | QNN_DLC | w8a8 | Qualcomm® QCS8450 (Proxy) | 0.854 ms | 0 - 67 MB | NPU
| RegNet-Y-800MF | QNN_DLC | w8a8 | Qualcomm® SA7255P | 1.618 ms | 0 - 46 MB | NPU
| RegNet-Y-800MF | QNN_DLC | w8a8 | Qualcomm® SA8295P | 1.133 ms | 0 - 45 MB | NPU
| RegNet-Y-800MF | QNN_DLC | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 0.384 ms | 0 - 50 MB | NPU
| RegNet-Y-800MF | QNN_DLC | w8a8 | Snapdragon® 7 Gen 4 Mobile | 0.729 ms | 0 - 46 MB | NPU
| RegNet-Y-800MF | QNN_DLC | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.308 ms | 0 - 50 MB | NPU
| RegNet-Y-800MF | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 0.915 ms | 0 - 93 MB | NPU
| RegNet-Y-800MF | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 4.029 ms | 0 - 63 MB | NPU
| RegNet-Y-800MF | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 1.384 ms | 0 - 3 MB | NPU
| RegNet-Y-800MF | TFLITE | float | Qualcomm® SA8775P | 7.985 ms | 0 - 64 MB | NPU
| RegNet-Y-800MF | TFLITE | float | Qualcomm® QCS9075 | 1.71 ms | 0 - 17 MB | NPU
| RegNet-Y-800MF | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 2.208 ms | 0 - 78 MB | NPU
| RegNet-Y-800MF | TFLITE | float | Qualcomm® SA7255P | 4.029 ms | 0 - 63 MB | NPU
| RegNet-Y-800MF | TFLITE | float | Qualcomm® SA8295P | 2.174 ms | 0 - 55 MB | NPU
| RegNet-Y-800MF | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 0.685 ms | 0 - 57 MB | NPU
| RegNet-Y-800MF | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.61 ms | 0 - 69 MB | NPU
| RegNet-Y-800MF | TFLITE | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.369 ms | 0 - 63 MB | NPU
| RegNet-Y-800MF | TFLITE | w8a8 | Qualcomm® QCS6490 | 1.332 ms | 0 - 9 MB | NPU
| RegNet-Y-800MF | TFLITE | w8a8 | Qualcomm® QCS8275 (Proxy) | 1.272 ms | 0 - 48 MB | NPU
| RegNet-Y-800MF | TFLITE | w8a8 | Qualcomm® QCS8550 (Proxy) | 0.513 ms | 0 - 2 MB | NPU
| RegNet-Y-800MF | TFLITE | w8a8 | Qualcomm® SA8775P | 0.759 ms | 0 - 52 MB | NPU
| RegNet-Y-800MF | TFLITE | w8a8 | Qualcomm® QCS9075 | 0.667 ms | 0 - 9 MB | NPU
| RegNet-Y-800MF | TFLITE | w8a8 | Qualcomm® QCM6690 | 2.368 ms | 0 - 42 MB | NPU
| RegNet-Y-800MF | TFLITE | w8a8 | Qualcomm® QCS8450 (Proxy) | 0.679 ms | 0 - 72 MB | NPU
| RegNet-Y-800MF | TFLITE | w8a8 | Qualcomm® SA7255P | 1.272 ms | 0 - 48 MB | NPU
| RegNet-Y-800MF | TFLITE | w8a8 | Qualcomm® SA8295P | 0.899 ms | 0 - 43 MB | NPU
| RegNet-Y-800MF | TFLITE | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 0.307 ms | 0 - 41 MB | NPU
| RegNet-Y-800MF | TFLITE | w8a8 | Snapdragon® 7 Gen 4 Mobile | 0.555 ms | 0 - 42 MB | NPU
| RegNet-Y-800MF | TFLITE | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.26 ms | 0 - 51 MB | NPU

## License
* The license for the original implementation of RegNet-Y-800MF can be found
  [here](https://github.com/pytorch/vision/blob/main/LICENSE).



## 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).