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README.md

@@ -36,7 +36,8 @@ More details on model performance across various devices, can be found
 
 | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
 | ---|---|---|---|---|---|---|---|
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 6.484 ms | 4 - 14 MB | FP16 | NPU |  [YOLOv8-Segmentation.tflite](https://huggingface.co/qualcomm/YOLOv8-Segmentation/blob/main/YOLOv8-Segmentation.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 6.539 ms | 0 - 35 MB | FP16 | NPU |  [YOLOv8-Segmentation.tflite](https://huggingface.co/qualcomm/YOLOv8-Segmentation/blob/main/YOLOv8-Segmentation.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 6.404 ms | 4 - 16 MB | FP16 | NPU |  [YOLOv8-Segmentation.so](https://huggingface.co/qualcomm/YOLOv8-Segmentation/blob/main/YOLOv8-Segmentation.so) 
 
 
 
@@ -95,6 +96,16 @@ device. This script does the following:
 python -m qai_hub_models.models.yolov8_seg.export
 ```
 
+```
+Profile Job summary of YOLOv8-Segmentation
+--------------------------------------------------
+Device: Snapdragon X Elite CRD (11)
+Estimated Inference Time: 6.57 ms
+Estimated Peak Memory Range: 4.70-4.70 MB
+Compute Units: NPU (333) | Total (333)
+
+
+```
 
 
 ## How does this work?