v0.49.1
Browse filesSee https://github.com/qualcomm/ai-hub-models/releases/v0.49.1 for changelog.
README.md
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Ultralytics YOLOv11 is a machine learning model that predicts bounding boxes and classes of objects in an image.
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This is based on the implementation of YOLOv11-Detection found [here](https://github.com/ultralytics/ultralytics/tree/main/ultralytics/models/yolo/detect).
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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/
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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.
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## Getting Started
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Due to licensing restrictions, we cannot distribute pre-exported model assets for this model.
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Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/
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- Custom weights (e.g., fine-tuned checkpoints)
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- Custom input shapes
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- Target device and runtime configurations
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See our repository for [YOLOv11-Detection on GitHub](https://github.com/qualcomm/ai-hub-models/
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## Model Details
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## Performance Summary
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| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
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|---|---|---|---|---|---|---
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| YOLOv11-Detection | ONNX | float | Snapdragon®
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| YOLOv11-Detection | ONNX | float | Snapdragon®
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| YOLOv11-Detection | ONNX | float | Snapdragon®
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| YOLOv11-Detection | ONNX | float |
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| YOLOv11-Detection | ONNX | float | Qualcomm®
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| YOLOv11-Detection | ONNX | float |
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| YOLOv11-Detection | ONNX | float | Snapdragon® 8 Elite
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| YOLOv11-Detection | ONNX | w8a16 | Snapdragon®
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| YOLOv11-Detection | ONNX | w8a16 | Snapdragon®
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| YOLOv11-Detection | ONNX | w8a16 | Snapdragon®
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| YOLOv11-Detection | ONNX | w8a16 |
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| YOLOv11-Detection | ONNX | w8a16 | Qualcomm®
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| YOLOv11-Detection | ONNX | w8a16 | Qualcomm®
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| YOLOv11-Detection | ONNX | w8a16 | Qualcomm®
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| YOLOv11-Detection | ONNX | w8a16 |
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| YOLOv11-Detection | ONNX | w8a16 | Snapdragon®
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| YOLOv11-Detection | ONNX | w8a16 | Snapdragon®
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| YOLOv11-Detection | ONNX | w8a8_mixed_int16 | Snapdragon®
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| YOLOv11-Detection | ONNX | w8a8_mixed_int16 | Snapdragon®
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| YOLOv11-Detection | ONNX | w8a8_mixed_int16 | Snapdragon®
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| YOLOv11-Detection | ONNX | w8a8_mixed_int16 |
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| YOLOv11-Detection | ONNX | w8a8_mixed_int16 | Qualcomm®
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| YOLOv11-Detection | ONNX | w8a8_mixed_int16 | Qualcomm®
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| YOLOv11-Detection | ONNX | w8a8_mixed_int16 | Qualcomm®
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| YOLOv11-Detection | ONNX | w8a8_mixed_int16 |
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| YOLOv11-Detection | ONNX | w8a8_mixed_int16 | Snapdragon®
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| YOLOv11-Detection | ONNX | w8a8_mixed_int16 | Snapdragon®
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| YOLOv11-Detection | QNN_DLC | float | Snapdragon®
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| YOLOv11-Detection | QNN_DLC | float | Snapdragon®
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| YOLOv11-Detection | QNN_DLC | float | Snapdragon®
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| YOLOv11-Detection | QNN_DLC | float |
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| YOLOv11-Detection | QNN_DLC | float | Qualcomm®
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| YOLOv11-Detection | QNN_DLC | float | Qualcomm®
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| YOLOv11-Detection | QNN_DLC | float | Qualcomm®
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| YOLOv11-Detection | QNN_DLC | float | Qualcomm®
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| YOLOv11-Detection | QNN_DLC | float | Qualcomm®
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| YOLOv11-Detection | QNN_DLC | float | Qualcomm®
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| YOLOv11-Detection | QNN_DLC | float |
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| YOLOv11-Detection | QNN_DLC | float | Snapdragon® 8 Elite
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| YOLOv11-Detection | QNN_DLC | w8a16 | Snapdragon®
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| YOLOv11-Detection | QNN_DLC | w8a16 | Snapdragon®
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| YOLOv11-Detection | QNN_DLC | w8a16 | Snapdragon®
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| YOLOv11-Detection | QNN_DLC | w8a16 |
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| YOLOv11-Detection | QNN_DLC | w8a16 | Qualcomm®
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| YOLOv11-Detection | QNN_DLC | w8a16 | Qualcomm®
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| YOLOv11-Detection | QNN_DLC | w8a16 | Qualcomm®
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| YOLOv11-Detection | QNN_DLC | w8a16 | Qualcomm®
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| YOLOv11-Detection | QNN_DLC | w8a16 | Qualcomm®
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| YOLOv11-Detection | QNN_DLC | w8a16 |
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| YOLOv11-Detection | QNN_DLC | w8a16 | Snapdragon®
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| YOLOv11-Detection | QNN_DLC | w8a16 | Snapdragon®
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| YOLOv11-Detection | TFLITE | float | Snapdragon® 8 Gen
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| YOLOv11-Detection | TFLITE | float |
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| YOLOv11-Detection | TFLITE | float | Qualcomm®
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| YOLOv11-Detection | TFLITE | float | Qualcomm®
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| YOLOv11-Detection | TFLITE | float | Qualcomm®
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| YOLOv11-Detection | TFLITE | float | Qualcomm®
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| YOLOv11-Detection | TFLITE | float | Qualcomm®
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| YOLOv11-Detection | TFLITE | float | Qualcomm®
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| YOLOv11-Detection | TFLITE | float |
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| YOLOv11-Detection | TFLITE | float | Snapdragon® 8 Elite
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| YOLOv11-Detection | TFLITE | w8a8 | Snapdragon® 8 Gen 3 Mobile | 1.105 ms | 0 - 53 MB | NPU
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| YOLOv11-Detection | TFLITE | w8a8 | Qualcomm® QCS6490 | 3.745 ms | 0 - 6 MB | NPU
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| YOLOv11-Detection | TFLITE | w8a8 | Qualcomm® QCS8275 (Proxy) | 3.426 ms | 0 - 39 MB | NPU
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| YOLOv11-Detection | TFLITE | w8a8 | Qualcomm® QCS8550 (Proxy) | 1.632 ms | 0 - 3 MB | NPU
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| YOLOv11-Detection | TFLITE | w8a8 | Qualcomm® SA8775P | 8.216 ms | 0 - 39 MB | NPU
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| YOLOv11-Detection | TFLITE | w8a8 | Qualcomm® QCS9075 | 2.011 ms | 0 - 6 MB | NPU
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| YOLOv11-Detection | TFLITE | w8a8 | Qualcomm® QCM6690 | 7.634 ms | 0 - 165 MB | NPU
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| YOLOv11-Detection | TFLITE | w8a8 | Qualcomm® QCS8450 (Proxy) | 1.881 ms | 0 - 55 MB | NPU
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| YOLOv11-Detection | TFLITE | w8a8 | Qualcomm® SA7255P | 3.426 ms | 0 - 39 MB | NPU
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| YOLOv11-Detection | TFLITE | w8a8 | Qualcomm® SA8295P | 2.471 ms | 0 - 37 MB | NPU
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| YOLOv11-Detection | TFLITE | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 0.819 ms | 0 - 38 MB | NPU
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| YOLOv11-Detection | TFLITE | w8a8 | Snapdragon® 7 Gen 4 Mobile | 1.696 ms | 0 - 155 MB | NPU
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| YOLOv11-Detection | TFLITE | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.728 ms | 0 - 44 MB | NPU
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## License
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* The license for the original implementation of YOLOv11-Detection can be found
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Ultralytics YOLOv11 is a machine learning model that predicts bounding boxes and classes of objects in an image.
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This is based on the implementation of YOLOv11-Detection found [here](https://github.com/ultralytics/ultralytics/tree/main/ultralytics/models/yolo/detect).
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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/tree/v0.49.1/qai_hub_models/models/yolov11_det) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).
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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.
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## Getting Started
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Due to licensing restrictions, we cannot distribute pre-exported model assets for this model.
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Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/tree/v0.49.1/qai_hub_models/models/yolov11_det) Python library to compile and export the model with your own:
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- Custom weights (e.g., fine-tuned checkpoints)
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- Custom input shapes
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- Target device and runtime configurations
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See our repository for [YOLOv11-Detection on GitHub](https://github.com/qualcomm/ai-hub-models/tree/v0.49.1/qai_hub_models/models/yolov11_det) for usage instructions.
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## Model Details
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## Performance Summary
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| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
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|---|---|---|---|---|---|---
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| YOLOv11-Detection | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 2.669 ms | 0 - 221 MB | NPU
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| YOLOv11-Detection | ONNX | float | Snapdragon® X2 Elite | 3.035 ms | 3 - 3 MB | NPU
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| YOLOv11-Detection | ONNX | float | Snapdragon® X Elite | 6.67 ms | 5 - 5 MB | NPU
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| YOLOv11-Detection | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 4.481 ms | 5 - 270 MB | NPU
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| YOLOv11-Detection | ONNX | float | Qualcomm® QCS8550 (Proxy) | 6.082 ms | 5 - 11 MB | NPU
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| YOLOv11-Detection | ONNX | float | Qualcomm® QCS9075 | 6.737 ms | 5 - 7 MB | NPU
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| YOLOv11-Detection | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 3.039 ms | 1 - 225 MB | NPU
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| YOLOv11-Detection | ONNX | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 2.168 ms | 0 - 81 MB | NPU
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| YOLOv11-Detection | ONNX | w8a16 | Snapdragon® X2 Elite | 2.33 ms | 0 - 0 MB | NPU
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| YOLOv11-Detection | ONNX | w8a16 | Snapdragon® X Elite | 5.764 ms | 2 - 2 MB | NPU
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| YOLOv11-Detection | ONNX | w8a16 | Snapdragon® 8 Gen 3 Mobile | 3.234 ms | 0 - 220 MB | NPU
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| YOLOv11-Detection | ONNX | w8a16 | Qualcomm® QCS6490 | 329.016 ms | 94 - 99 MB | CPU
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| YOLOv11-Detection | ONNX | w8a16 | Qualcomm® QCS8550 (Proxy) | 5.246 ms | 2 - 7 MB | NPU
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| YOLOv11-Detection | ONNX | w8a16 | Qualcomm® QCS9075 | 6.119 ms | 2 - 5 MB | NPU
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| YOLOv11-Detection | ONNX | w8a16 | Qualcomm® QCM6690 | 165.375 ms | 84 - 94 MB | CPU
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| YOLOv11-Detection | ONNX | w8a16 | Snapdragon® 8 Elite For Galaxy Mobile | 2.377 ms | 0 - 73 MB | NPU
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| YOLOv11-Detection | ONNX | w8a16 | Snapdragon® 7 Gen 4 Mobile | 146.642 ms | 97 - 106 MB | CPU
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| YOLOv11-Detection | ONNX | w8a8_mixed_int16 | Snapdragon® 8 Elite Gen 5 Mobile | 9.757 ms | 5 - 510 MB | NPU
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| YOLOv11-Detection | ONNX | w8a8_mixed_int16 | Snapdragon® X2 Elite | 11.636 ms | 7 - 7 MB | NPU
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| YOLOv11-Detection | ONNX | w8a8_mixed_int16 | Snapdragon® X Elite | 17.866 ms | 5 - 5 MB | NPU
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| YOLOv11-Detection | ONNX | w8a8_mixed_int16 | Snapdragon® 8 Gen 3 Mobile | 11.758 ms | 5 - 628 MB | NPU
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| YOLOv11-Detection | ONNX | w8a8_mixed_int16 | Qualcomm® QCS6490 | 142.288 ms | 62 - 72 MB | CPU
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| YOLOv11-Detection | ONNX | w8a8_mixed_int16 | Qualcomm® QCS8550 (Proxy) | 16.79 ms | 4 - 7 MB | NPU
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| YOLOv11-Detection | ONNX | w8a8_mixed_int16 | Qualcomm® QCS9075 | 23.393 ms | 4 - 6 MB | NPU
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| YOLOv11-Detection | ONNX | w8a8_mixed_int16 | Qualcomm® QCM6690 | 83.861 ms | 62 - 74 MB | CPU
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| YOLOv11-Detection | ONNX | w8a8_mixed_int16 | Snapdragon® 8 Elite For Galaxy Mobile | 9.876 ms | 2 - 503 MB | NPU
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| YOLOv11-Detection | ONNX | w8a8_mixed_int16 | Snapdragon® 7 Gen 4 Mobile | 74.776 ms | 66 - 79 MB | CPU
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| YOLOv11-Detection | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.869 ms | 1 - 186 MB | NPU
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| YOLOv11-Detection | QNN_DLC | float | Snapdragon® X2 Elite | 2.551 ms | 5 - 5 MB | NPU
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| YOLOv11-Detection | QNN_DLC | float | Snapdragon® X Elite | 4.297 ms | 5 - 5 MB | NPU
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| YOLOv11-Detection | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 2.891 ms | 5 - 214 MB | NPU
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| YOLOv11-Detection | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 12.701 ms | 1 - 183 MB | NPU
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| YOLOv11-Detection | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 3.896 ms | 5 - 7 MB | NPU
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| YOLOv11-Detection | QNN_DLC | float | Qualcomm® SA8775P | 5.281 ms | 0 - 183 MB | NPU
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| YOLOv11-Detection | QNN_DLC | float | Qualcomm® QCS9075 | 5.016 ms | 5 - 11 MB | NPU
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| YOLOv11-Detection | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 8.426 ms | 5 - 196 MB | NPU
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| YOLOv11-Detection | QNN_DLC | float | Qualcomm® SA7255P | 12.701 ms | 1 - 183 MB | NPU
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| YOLOv11-Detection | QNN_DLC | float | Qualcomm® SA8295P | 8.62 ms | 1 - 167 MB | NPU
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| YOLOv11-Detection | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 2.249 ms | 1 - 187 MB | NPU
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| YOLOv11-Detection | QNN_DLC | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 1.768 ms | 2 - 184 MB | NPU
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| YOLOv11-Detection | QNN_DLC | w8a16 | Snapdragon® X2 Elite | 2.182 ms | 2 - 2 MB | NPU
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| YOLOv11-Detection | QNN_DLC | w8a16 | Snapdragon® X Elite | 4.626 ms | 2 - 2 MB | NPU
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| YOLOv11-Detection | QNN_DLC | w8a16 | Snapdragon® 8 Gen 3 Mobile | 2.98 ms | 2 - 203 MB | NPU
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| YOLOv11-Detection | QNN_DLC | w8a16 | Qualcomm® QCS8275 (Proxy) | 8.011 ms | 0 - 173 MB | NPU
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| YOLOv11-Detection | QNN_DLC | w8a16 | Qualcomm® QCS8550 (Proxy) | 4.261 ms | 2 - 4 MB | NPU
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| YOLOv11-Detection | QNN_DLC | w8a16 | Qualcomm® SA8775P | 20.282 ms | 1 - 173 MB | NPU
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| YOLOv11-Detection | QNN_DLC | w8a16 | Qualcomm® QCS9075 | 4.888 ms | 1 - 5 MB | NPU
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| YOLOv11-Detection | QNN_DLC | w8a16 | Qualcomm® QCM6690 | 18.254 ms | 2 - 182 MB | NPU
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| YOLOv11-Detection | QNN_DLC | w8a16 | Qualcomm® SA7255P | 8.011 ms | 0 - 173 MB | NPU
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| YOLOv11-Detection | QNN_DLC | w8a16 | Snapdragon® 8 Elite For Galaxy Mobile | 1.938 ms | 2 - 178 MB | NPU
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| YOLOv11-Detection | QNN_DLC | w8a16 | Snapdragon® 7 Gen 4 Mobile | 4.525 ms | 2 - 180 MB | NPU
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| YOLOv11-Detection | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.54 ms | 0 - 88 MB | NPU
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| YOLOv11-Detection | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 2.613 ms | 0 - 109 MB | NPU
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| YOLOv11-Detection | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 12.283 ms | 0 - 82 MB | NPU
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| YOLOv11-Detection | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 3.625 ms | 0 - 12 MB | NPU
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| YOLOv11-Detection | TFLITE | float | Qualcomm® SA8775P | 20.522 ms | 0 - 90 MB | NPU
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| YOLOv11-Detection | TFLITE | float | Qualcomm® QCS9075 | 4.721 ms | 0 - 13 MB | NPU
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| YOLOv11-Detection | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 7.099 ms | 0 - 77 MB | NPU
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| YOLOv11-Detection | TFLITE | float | Qualcomm® SA7255P | 12.283 ms | 0 - 82 MB | NPU
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| YOLOv11-Detection | TFLITE | float | Qualcomm® SA8295P | 8.039 ms | 0 - 52 MB | NPU
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| YOLOv11-Detection | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 1.959 ms | 0 - 75 MB | NPU
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| YOLOv11-Detection | TFLITE | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.728 ms | 0 - 44 MB | NPU
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| YOLOv11-Detection | TFLITE | w8a8 | Snapdragon® 8 Gen 3 Mobile | 1.105 ms | 0 - 53 MB | NPU
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| YOLOv11-Detection | TFLITE | w8a8 | Qualcomm® QCS6490 | 3.991 ms | 0 - 6 MB | NPU
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| YOLOv11-Detection | TFLITE | w8a8 | Qualcomm® QCS8275 (Proxy) | 3.418 ms | 0 - 39 MB | NPU
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| YOLOv11-Detection | TFLITE | w8a8 | Qualcomm® QCS8550 (Proxy) | 1.636 ms | 0 - 2 MB | NPU
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| YOLOv11-Detection | TFLITE | w8a8 | Qualcomm® SA8775P | 2.079 ms | 0 - 43 MB | NPU
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| YOLOv11-Detection | TFLITE | w8a8 | Qualcomm® QCS9075 | 2.017 ms | 0 - 6 MB | NPU
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| YOLOv11-Detection | TFLITE | w8a8 | Qualcomm® QCM6690 | 7.643 ms | 0 - 165 MB | NPU
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| YOLOv11-Detection | TFLITE | w8a8 | Qualcomm® QCS8450 (Proxy) | 1.932 ms | 0 - 55 MB | NPU
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| 117 |
+
| YOLOv11-Detection | TFLITE | w8a8 | Qualcomm® SA7255P | 3.418 ms | 0 - 39 MB | NPU
|
| 118 |
+
| YOLOv11-Detection | TFLITE | w8a8 | Qualcomm® SA8295P | 2.472 ms | 0 - 37 MB | NPU
|
| 119 |
+
| YOLOv11-Detection | TFLITE | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 0.831 ms | 0 - 43 MB | NPU
|
| 120 |
+
| YOLOv11-Detection | TFLITE | w8a8 | Snapdragon® 7 Gen 4 Mobile | 1.704 ms | 0 - 158 MB | NPU
|
| 121 |
|
| 122 |
## License
|
| 123 |
* The license for the original implementation of YOLOv11-Detection can be found
|