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README.md

@@ -33,8 +33,8 @@ 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 | 7.377 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 | QNN Model Library | 6.398 ms | 6 - 16 MB | FP16 | NPU |  [YOLOv8-Segmentation.so](https://huggingface.co/qualcomm/YOLOv8-Segmentation/blob/main/YOLOv8-Segmentation.so) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 7.371 ms | 4 - 7 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 | 6.414 ms | 4 - 14 MB | FP16 | NPU |  [YOLOv8-Segmentation.so](https://huggingface.co/qualcomm/YOLOv8-Segmentation/blob/main/YOLOv8-Segmentation.so) 
 
 
 ## Installation
@@ -96,7 +96,7 @@ python -m qai_hub_models.models.yolov8_seg.export
 Profile Job summary of YOLOv8-Segmentation
 --------------------------------------------------
 Device: Snapdragon X Elite CRD (11)
-Estimated Inference Time: 7.60 ms
+Estimated Inference Time: 7.57 ms
 Estimated Peak Memory Range: 4.70-4.70 MB
 Compute Units: NPU (333) | Total (333)