---
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/resnext50/web-assets/model_demo.png)

# ResNeXt50: Optimized for Qualcomm Devices

ResNeXt50 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 ResNeXt50 found [here](https://github.com/pytorch/vision/blob/main/torchvision/models/resnet.py).
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/resnext50) 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/resnext50/releases/v0.52.0/resnext50-onnx-float.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/resnext50/releases/v0.52.0/resnext50-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/resnext50/releases/v0.52.0/resnext50-qnn_dlc-float.zip)
| QNN_DLC | w8a8 | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnext50/releases/v0.52.0/resnext50-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/resnext50/releases/v0.52.0/resnext50-tflite-float.zip)
| TFLITE | w8a8 | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/resnext50/releases/v0.52.0/resnext50-tflite-w8a8.zip)

For more device-specific assets and performance metrics, visit **[ResNeXt50 on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/resnext50)**.


### 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/resnext50) 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 [ResNeXt50 on GitHub](https://github.com/qualcomm/ai-hub-models/blob/main/src/qai_hub_models/models/resnext50) for usage instructions.

## Model Details

**Model Type:** Model_use_case.image_classification

**Model Stats:**
- Model checkpoint: Imagenet
- Input resolution: 224x224
- Number of parameters: 25.0M
- Model size (float): 95.4 MB
- Model size (w8a8): 24.8 MB

## Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
|---|---|---|---|---|---|---
| ResNeXt50 | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.132 ms | 1 - 85 MB | NPU
| ResNeXt50 | ONNX | float | Snapdragon® X2 Elite | 1.098 ms | 50 - 50 MB | NPU
| ResNeXt50 | ONNX | float | Snapdragon® X Elite | 2.422 ms | 50 - 50 MB | NPU
| ResNeXt50 | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 1.669 ms | 0 - 150 MB | NPU
| ResNeXt50 | ONNX | float | Qualcomm® QCS8550 (Proxy) | 2.284 ms | 1 - 9 MB | NPU
| ResNeXt50 | ONNX | float | Qualcomm® QCS9075 | 3.453 ms | 0 - 4 MB | NPU
| ResNeXt50 | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 1.383 ms | 0 - 85 MB | NPU
| ResNeXt50 | ONNX | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.603 ms | 0 - 79 MB | NPU
| ResNeXt50 | ONNX | w8a8 | Snapdragon® X2 Elite | 0.505 ms | 25 - 25 MB | NPU
| ResNeXt50 | ONNX | w8a8 | Snapdragon® X Elite | 1.281 ms | 25 - 25 MB | NPU
| ResNeXt50 | ONNX | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.814 ms | 0 - 100 MB | NPU
| ResNeXt50 | ONNX | w8a8 | Qualcomm® QCS6490 | 46.441 ms | 8 - 24 MB | CPU
| ResNeXt50 | ONNX | w8a8 | Qualcomm® QCS8550 (Proxy) | 1.128 ms | 0 - 33 MB | NPU
| ResNeXt50 | ONNX | w8a8 | Qualcomm® QCS9075 | 1.233 ms | 0 - 3 MB | NPU
| ResNeXt50 | ONNX | w8a8 | Qualcomm® QCM6690 | 26.538 ms | 3 - 12 MB | CPU
| ResNeXt50 | ONNX | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 0.692 ms | 0 - 68 MB | NPU
| ResNeXt50 | ONNX | w8a8 | Snapdragon® 7 Gen 4 Mobile | 20.706 ms | 5 - 14 MB | CPU
| ResNeXt50 | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.167 ms | 1 - 75 MB | NPU
| ResNeXt50 | QNN_DLC | float | Snapdragon® X2 Elite | 1.415 ms | 1 - 1 MB | NPU
| ResNeXt50 | QNN_DLC | float | Snapdragon® X Elite | 2.692 ms | 1 - 1 MB | NPU
| ResNeXt50 | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 1.797 ms | 0 - 132 MB | NPU
| ResNeXt50 | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 12.02 ms | 1 - 71 MB | NPU
| ResNeXt50 | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 2.568 ms | 1 - 3 MB | NPU
| ResNeXt50 | QNN_DLC | float | Qualcomm® SA8775P | 3.832 ms | 1 - 72 MB | NPU
| ResNeXt50 | QNN_DLC | float | Qualcomm® QCS9075 | 3.633 ms | 1 - 3 MB | NPU
| ResNeXt50 | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 4.01 ms | 0 - 112 MB | NPU
| ResNeXt50 | QNN_DLC | float | Qualcomm® SA7255P | 12.02 ms | 1 - 71 MB | NPU
| ResNeXt50 | QNN_DLC | float | Qualcomm® SA8295P | 4.11 ms | 0 - 51 MB | NPU
| ResNeXt50 | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 1.466 ms | 1 - 74 MB | NPU
| ResNeXt50 | QNN_DLC | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.541 ms | 0 - 75 MB | NPU
| ResNeXt50 | QNN_DLC | w8a8 | Snapdragon® X2 Elite | 0.621 ms | 0 - 0 MB | NPU
| ResNeXt50 | QNN_DLC | w8a8 | Snapdragon® X Elite | 1.239 ms | 0 - 0 MB | NPU
| ResNeXt50 | QNN_DLC | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.787 ms | 0 - 101 MB | NPU
| ResNeXt50 | QNN_DLC | w8a8 | Qualcomm® QCS6490 | 3.111 ms | 0 - 2 MB | NPU
| ResNeXt50 | QNN_DLC | w8a8 | Qualcomm® QCS8275 (Proxy) | 2.438 ms | 0 - 69 MB | NPU
| ResNeXt50 | QNN_DLC | w8a8 | Qualcomm® QCS8550 (Proxy) | 1.105 ms | 0 - 2 MB | NPU
| ResNeXt50 | QNN_DLC | w8a8 | Qualcomm® SA8775P | 1.449 ms | 0 - 72 MB | NPU
| ResNeXt50 | QNN_DLC | w8a8 | Qualcomm® QCS9075 | 1.203 ms | 0 - 2 MB | NPU
| ResNeXt50 | QNN_DLC | w8a8 | Qualcomm® QCM6690 | 7.601 ms | 0 - 194 MB | NPU
| ResNeXt50 | QNN_DLC | w8a8 | Qualcomm® QCS8450 (Proxy) | 1.457 ms | 0 - 100 MB | NPU
| ResNeXt50 | QNN_DLC | w8a8 | Qualcomm® SA7255P | 2.438 ms | 0 - 69 MB | NPU
| ResNeXt50 | QNN_DLC | w8a8 | Qualcomm® SA8295P | 1.77 ms | 0 - 68 MB | NPU
| ResNeXt50 | QNN_DLC | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 0.636 ms | 0 - 73 MB | NPU
| ResNeXt50 | QNN_DLC | w8a8 | Snapdragon® 7 Gen 4 Mobile | 1.375 ms | 0 - 75 MB | NPU
| ResNeXt50 | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.178 ms | 0 - 116 MB | NPU
| ResNeXt50 | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 1.771 ms | 0 - 177 MB | NPU
| ResNeXt50 | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 12.032 ms | 0 - 112 MB | NPU
| ResNeXt50 | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 2.473 ms | 0 - 2 MB | NPU
| ResNeXt50 | TFLITE | float | Qualcomm® SA8775P | 3.84 ms | 0 - 113 MB | NPU
| ResNeXt50 | TFLITE | float | Qualcomm® QCS9075 | 3.686 ms | 0 - 52 MB | NPU
| ResNeXt50 | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 4.004 ms | 0 - 151 MB | NPU
| ResNeXt50 | TFLITE | float | Qualcomm® SA7255P | 12.032 ms | 0 - 112 MB | NPU
| ResNeXt50 | TFLITE | float | Qualcomm® SA8295P | 4.146 ms | 0 - 87 MB | NPU
| ResNeXt50 | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 1.435 ms | 0 - 116 MB | NPU
| ResNeXt50 | TFLITE | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.485 ms | 0 - 73 MB | NPU
| ResNeXt50 | TFLITE | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.676 ms | 0 - 99 MB | NPU
| ResNeXt50 | TFLITE | w8a8 | Qualcomm® QCS6490 | 2.807 ms | 0 - 27 MB | NPU
| ResNeXt50 | TFLITE | w8a8 | Qualcomm® QCS8275 (Proxy) | 2.215 ms | 0 - 70 MB | NPU
| ResNeXt50 | TFLITE | w8a8 | Qualcomm® QCS8550 (Proxy) | 0.894 ms | 0 - 2 MB | NPU
| ResNeXt50 | TFLITE | w8a8 | Qualcomm® SA8775P | 1.276 ms | 0 - 71 MB | NPU
| ResNeXt50 | TFLITE | w8a8 | Qualcomm® QCS9075 | 0.992 ms | 0 - 27 MB | NPU
| ResNeXt50 | TFLITE | w8a8 | Qualcomm® QCM6690 | 7.047 ms | 0 - 198 MB | NPU
| ResNeXt50 | TFLITE | w8a8 | Qualcomm® QCS8450 (Proxy) | 1.286 ms | 0 - 99 MB | NPU
| ResNeXt50 | TFLITE | w8a8 | Qualcomm® SA7255P | 2.215 ms | 0 - 70 MB | NPU
| ResNeXt50 | TFLITE | w8a8 | Qualcomm® SA8295P | 1.556 ms | 0 - 65 MB | NPU
| ResNeXt50 | TFLITE | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 0.551 ms | 0 - 64 MB | NPU
| ResNeXt50 | TFLITE | w8a8 | Snapdragon® 7 Gen 4 Mobile | 1.218 ms | 0 - 70 MB | NPU

## License
* The license for the original implementation of ResNeXt50 can be found
  [here](https://github.com/pytorch/vision/blob/main/LICENSE).

## References
* [Aggregated Residual Transformations for Deep Neural Networks](https://arxiv.org/abs/1611.05431)
* [Source Model Implementation](https://github.com/pytorch/vision/blob/main/torchvision/models/resnet.py)

## 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).