YOLOv10-Detection: Optimized for Qualcomm Devices
Ultralytics YOLOv10 is a machine learning model that predicts bounding boxes and classes of objects in an image.
This is based on the implementation of YOLOv10-Detection found here. This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the Qualcomm® AI Hub Models library to export with custom configurations. More details on model performance across various devices, can be found here.
Qualcomm AI Hub Models uses Qualcomm AI Hub Workbench to compile, profile, and evaluate this model. Sign up 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 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 YOLOv10-Detection on GitHub for usage instructions.
Model Details
Model Type: Model_use_case.object_detection
Model Stats:
- Model checkpoint: YOLOv10-N
- Input resolution: 640x640
- Number of parameters: 2.33M
- Model size (float): 8.95 MB
- Model size (w8a8): 2.55 MB
- Model size (w8a16): 3.04 MB
Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |
|---|---|---|---|---|---|---|
| YOLOv10-Detection | ONNX | float | Snapdragon® X Elite | 5.821 ms | 5 - 5 MB | NPU |
| YOLOv10-Detection | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 3.766 ms | 5 - 213 MB | NPU |
| YOLOv10-Detection | ONNX | float | Qualcomm® QCS8550 (Proxy) | 5.539 ms | 5 - 9 MB | NPU |
| YOLOv10-Detection | ONNX | float | Qualcomm® QCS9075 | 7.244 ms | 5 - 7 MB | NPU |
| YOLOv10-Detection | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 3.472 ms | 0 - 164 MB | NPU |
| YOLOv10-Detection | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 2.509 ms | 0 - 156 MB | NPU |
| YOLOv10-Detection | ONNX | w8a16 | Snapdragon® X Elite | 5.529 ms | 2 - 2 MB | NPU |
| YOLOv10-Detection | ONNX | w8a16 | Snapdragon® 8 Gen 3 Mobile | 3.335 ms | 0 - 165 MB | NPU |
| YOLOv10-Detection | ONNX | w8a16 | Qualcomm® QCS6490 | 359.505 ms | 66 - 72 MB | CPU |
| YOLOv10-Detection | ONNX | w8a16 | Qualcomm® QCS8550 (Proxy) | 5.346 ms | 1 - 164 MB | NPU |
| YOLOv10-Detection | ONNX | w8a16 | Qualcomm® QCS9075 | 6.797 ms | 2 - 5 MB | NPU |
| YOLOv10-Detection | ONNX | w8a16 | Qualcomm® QCM6690 | 177.917 ms | 57 - 67 MB | CPU |
| YOLOv10-Detection | ONNX | w8a16 | Snapdragon® 8 Elite For Galaxy Mobile | 2.557 ms | 2 - 142 MB | NPU |
| YOLOv10-Detection | ONNX | w8a16 | Snapdragon® 7 Gen 4 Mobile | 157.609 ms | 68 - 77 MB | CPU |
| YOLOv10-Detection | ONNX | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 2.294 ms | 0 - 141 MB | NPU |
| YOLOv10-Detection | QNN_DLC | float | Snapdragon® X Elite | 4.417 ms | 5 - 5 MB | NPU |
| YOLOv10-Detection | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 2.939 ms | 5 - 254 MB | NPU |
| YOLOv10-Detection | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 13.141 ms | 3 - 201 MB | NPU |
| YOLOv10-Detection | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 4.019 ms | 5 - 12 MB | NPU |
| YOLOv10-Detection | QNN_DLC | float | Qualcomm® SA8775P | 5.44 ms | 1 - 202 MB | NPU |
| YOLOv10-Detection | QNN_DLC | float | Qualcomm® QCS9075 | 5.083 ms | 5 - 11 MB | NPU |
| YOLOv10-Detection | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 9.216 ms | 4 - 197 MB | NPU |
| YOLOv10-Detection | QNN_DLC | float | Qualcomm® SA7255P | 13.141 ms | 3 - 201 MB | NPU |
| YOLOv10-Detection | QNN_DLC | float | Qualcomm® SA8295P | 8.739 ms | 1 - 168 MB | NPU |
| YOLOv10-Detection | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 2.195 ms | 5 - 211 MB | NPU |
| YOLOv10-Detection | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.86 ms | 5 - 208 MB | NPU |
| YOLOv10-Detection | QNN_DLC | w8a16 | Snapdragon® X Elite | 4.624 ms | 2 - 2 MB | NPU |
| YOLOv10-Detection | QNN_DLC | w8a16 | Snapdragon® 8 Gen 3 Mobile | 2.995 ms | 0 - 200 MB | NPU |
| YOLOv10-Detection | QNN_DLC | w8a16 | Qualcomm® QCS8275 (Proxy) | 7.996 ms | 1 - 174 MB | NPU |
| YOLOv10-Detection | QNN_DLC | w8a16 | Qualcomm® QCS8550 (Proxy) | 4.248 ms | 2 - 4 MB | NPU |
| YOLOv10-Detection | QNN_DLC | w8a16 | Qualcomm® SA8775P | 20.28 ms | 0 - 173 MB | NPU |
| YOLOv10-Detection | QNN_DLC | w8a16 | Qualcomm® QCS9075 | 4.734 ms | 1 - 5 MB | NPU |
| YOLOv10-Detection | QNN_DLC | w8a16 | Qualcomm® QCM6690 | 20.613 ms | 2 - 182 MB | NPU |
| YOLOv10-Detection | QNN_DLC | w8a16 | Qualcomm® SA7255P | 7.996 ms | 1 - 174 MB | NPU |
| YOLOv10-Detection | QNN_DLC | w8a16 | Snapdragon® 8 Elite For Galaxy Mobile | 2.075 ms | 2 - 176 MB | NPU |
| YOLOv10-Detection | QNN_DLC | w8a16 | Snapdragon® 7 Gen 4 Mobile | 4.406 ms | 2 - 177 MB | NPU |
| YOLOv10-Detection | QNN_DLC | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 1.767 ms | 2 - 184 MB | NPU |
| YOLOv10-Detection | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 2.647 ms | 0 - 173 MB | NPU |
| YOLOv10-Detection | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 12.668 ms | 0 - 107 MB | NPU |
| YOLOv10-Detection | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 3.692 ms | 0 - 3 MB | NPU |
| YOLOv10-Detection | TFLITE | float | Qualcomm® SA8775P | 5.095 ms | 0 - 108 MB | NPU |
| YOLOv10-Detection | TFLITE | float | Qualcomm® QCS9075 | 4.8 ms | 0 - 13 MB | NPU |
| YOLOv10-Detection | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 7.759 ms | 0 - 195 MB | NPU |
| YOLOv10-Detection | TFLITE | float | Qualcomm® SA7255P | 12.668 ms | 0 - 107 MB | NPU |
| YOLOv10-Detection | TFLITE | float | Qualcomm® SA8295P | 8.116 ms | 0 - 171 MB | NPU |
| YOLOv10-Detection | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 1.996 ms | 0 - 115 MB | NPU |
| YOLOv10-Detection | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.557 ms | 0 - 109 MB | NPU |
License
- The license for the original implementation of YOLOv10-Detection can be found here.
References
Community
- Join our AI Hub Slack community to collaborate, post questions and learn more about on-device AI.
- For questions or feedback please reach out to us.
