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Yolo-v6

Object Detection
PyTorch
real_time
android
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Yolo-v6
File size: 7,201 Bytes
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---
library_name: pytorch
license: other
tags:
- real_time
- android
pipeline_tag: object-detection

---

![](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/yolov6/web-assets/model_demo.png)

# Yolo-v6: Optimized for Qualcomm Devices

YoloV6 is a machine learning model that predicts bounding boxes and classes of objects in an image.

This is based on the implementation of Yolo-v6 found [here](https://github.com/meituan/YOLOv6/).
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/yolov6) 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
Due to licensing restrictions, we cannot distribute pre-exported model assets for this model.
Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/main/src/qai_hub_models/models/yolov6) 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

See our repository for [Yolo-v6 on GitHub](https://github.com/qualcomm/ai-hub-models/blob/main/src/qai_hub_models/models/yolov6) for usage instructions.


## Model Details

**Model Type:** Model_use_case.object_detection

**Model Stats:**
- Model checkpoint: YoloV6-N
- Input resolution: 640x640
- Number of parameters: 4.68M
- Model size (float): 17.9 MB
- Model size (w8a8): 4.68 MB
- Model size (w8a16): 5.03 MB

## Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
|---|---|---|---|---|---|---
| Yolo-v6 | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 3.997 ms | 5 - 172 MB | NPU
| Yolo-v6 | ONNX | float | Snapdragon® X2 Elite | 3.678 ms | 14 - 14 MB | NPU
| Yolo-v6 | ONNX | float | Snapdragon® X Elite | 8.342 ms | 14 - 14 MB | NPU
| Yolo-v6 | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 5.5 ms | 5 - 203 MB | NPU
| Yolo-v6 | ONNX | float | Qualcomm® QCS8550 (Proxy) | 8.111 ms | 0 - 17 MB | NPU
| Yolo-v6 | ONNX | float | Qualcomm® QCS9075 | 9.655 ms | 5 - 7 MB | NPU
| Yolo-v6 | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 4.317 ms | 1 - 170 MB | NPU
| Yolo-v6 | ONNX | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 1.841 ms | 0 - 187 MB | NPU
| Yolo-v6 | ONNX | w8a16 | Snapdragon® X2 Elite | 2.009 ms | 5 - 5 MB | NPU
| Yolo-v6 | ONNX | w8a16 | Snapdragon® X Elite | 4.529 ms | 3 - 3 MB | NPU
| Yolo-v6 | ONNX | w8a16 | Snapdragon® 8 Gen 3 Mobile | 2.677 ms | 0 - 221 MB | NPU
| Yolo-v6 | ONNX | w8a16 | Qualcomm® QCS6490 | 286.42 ms | 40 - 45 MB | CPU
| Yolo-v6 | ONNX | w8a16 | Qualcomm® QCS8550 (Proxy) | 4.08 ms | 0 - 7 MB | NPU
| Yolo-v6 | ONNX | w8a16 | Qualcomm® QCS9075 | 4.858 ms | 2 - 5 MB | NPU
| Yolo-v6 | ONNX | w8a16 | Qualcomm® QCM6690 | 147.177 ms | 42 - 50 MB | CPU
| Yolo-v6 | ONNX | w8a16 | Snapdragon® 8 Elite For Galaxy Mobile | 2.079 ms | 0 - 181 MB | NPU
| Yolo-v6 | ONNX | w8a16 | Snapdragon® 7 Gen 4 Mobile | 128.373 ms | 44 - 52 MB | CPU
| Yolo-v6 | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 3.113 ms | 5 - 161 MB | NPU
| Yolo-v6 | QNN_DLC | float | Snapdragon® X2 Elite | 3.205 ms | 5 - 5 MB | NPU
| Yolo-v6 | QNN_DLC | float | Snapdragon® X Elite | 6.244 ms | 5 - 5 MB | NPU
| Yolo-v6 | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 4.482 ms | 0 - 182 MB | NPU
| Yolo-v6 | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 16.205 ms | 0 - 153 MB | NPU
| Yolo-v6 | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 6.139 ms | 5 - 19 MB | NPU
| Yolo-v6 | QNN_DLC | float | Qualcomm® SA8775P | 7.67 ms | 0 - 157 MB | NPU
| Yolo-v6 | QNN_DLC | float | Qualcomm® QCS9075 | 7.742 ms | 7 - 13 MB | NPU
| Yolo-v6 | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 8.901 ms | 5 - 188 MB | NPU
| Yolo-v6 | QNN_DLC | float | Qualcomm® SA7255P | 16.205 ms | 0 - 153 MB | NPU
| Yolo-v6 | QNN_DLC | float | Qualcomm® SA8295P | 9.081 ms | 3 - 155 MB | NPU
| Yolo-v6 | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 3.326 ms | 0 - 156 MB | NPU
| Yolo-v6 | QNN_DLC | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 0.949 ms | 0 - 40 MB | NPU
| Yolo-v6 | QNN_DLC | w8a16 | Snapdragon® X2 Elite | 1.403 ms | 2 - 2 MB | NPU
| Yolo-v6 | QNN_DLC | w8a16 | Snapdragon® X Elite | 2.492 ms | 2 - 2 MB | NPU
| Yolo-v6 | QNN_DLC | w8a16 | Snapdragon® 8 Gen 3 Mobile | 1.503 ms | 2 - 57 MB | NPU
| Yolo-v6 | QNN_DLC | w8a16 | Qualcomm® QCS6490 | 6.586 ms | 2 - 6 MB | NPU
| Yolo-v6 | QNN_DLC | w8a16 | Qualcomm® QCS8275 (Proxy) | 5.353 ms | 1 - 38 MB | NPU
| Yolo-v6 | QNN_DLC | w8a16 | Qualcomm® QCS8550 (Proxy) | 2.205 ms | 2 - 3 MB | NPU
| Yolo-v6 | QNN_DLC | w8a16 | Qualcomm® SA8775P | 2.819 ms | 1 - 41 MB | NPU
| Yolo-v6 | QNN_DLC | w8a16 | Qualcomm® QCS9075 | 2.58 ms | 1 - 5 MB | NPU
| Yolo-v6 | QNN_DLC | w8a16 | Qualcomm® QCM6690 | 17.547 ms | 2 - 152 MB | NPU
| Yolo-v6 | QNN_DLC | w8a16 | Qualcomm® QCS8450 (Proxy) | 2.817 ms | 2 - 58 MB | NPU
| Yolo-v6 | QNN_DLC | w8a16 | Qualcomm® SA7255P | 5.353 ms | 1 - 38 MB | NPU
| Yolo-v6 | QNN_DLC | w8a16 | Qualcomm® SA8295P | 3.478 ms | 2 - 37 MB | NPU
| Yolo-v6 | QNN_DLC | w8a16 | Snapdragon® 8 Elite For Galaxy Mobile | 1.15 ms | 2 - 48 MB | NPU
| Yolo-v6 | QNN_DLC | w8a16 | Snapdragon® 7 Gen 4 Mobile | 2.735 ms | 0 - 150 MB | NPU
| Yolo-v6 | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 3.389 ms | 0 - 166 MB | NPU
| Yolo-v6 | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 11.18 ms | 4 - 77 MB | GPU
| Yolo-v6 | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 56.698 ms | 6 - 35 MB | GPU
| Yolo-v6 | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 14.579 ms | 5 - 24 MB | GPU
| Yolo-v6 | TFLITE | float | Qualcomm® SA8775P | 23.976 ms | 6 - 61 MB | GPU
| Yolo-v6 | TFLITE | float | Qualcomm® QCS9075 | 7.896 ms | 0 - 18 MB | NPU
| Yolo-v6 | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 18.4 ms | 6 - 84 MB | GPU
| Yolo-v6 | TFLITE | float | Qualcomm® SA7255P | 56.698 ms | 6 - 35 MB | GPU
| Yolo-v6 | TFLITE | float | Qualcomm® SA8295P | 19.09 ms | 5 - 61 MB | GPU
| Yolo-v6 | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 3.768 ms | 0 - 163 MB | NPU

## License
* The license for the original implementation of Yolo-v6 can be found
  [here](https://github.com/meituan/YOLOv6/blob/47625514e7480706a46ff3c0cd0252907ac12f22/LICENSE).

## References
* [YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications](https://arxiv.org/abs/2209.02976)
* [Source Model Implementation](https://github.com/meituan/YOLOv6/)

## 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).