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README.md

@@ -34,8 +34,8 @@ 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 | 160.694 ms | 6 - 219 MB | FP16 | NPU |  [Unet-Segmentation.tflite](https://huggingface.co/qualcomm/Unet-Segmentation/blob/main/Unet-Segmentation.tflite) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 146.509 ms | 10 - 43 MB | FP16 | NPU |  [Unet-Segmentation.so](https://huggingface.co/qualcomm/Unet-Segmentation/blob/main/Unet-Segmentation.so) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 159.721 ms | 6 - 220 MB | FP16 | NPU |  [Unet-Segmentation.tflite](https://huggingface.co/qualcomm/Unet-Segmentation/blob/main/Unet-Segmentation.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 143.885 ms | 9 - 35 MB | FP16 | NPU |  [Unet-Segmentation.so](https://huggingface.co/qualcomm/Unet-Segmentation/blob/main/Unet-Segmentation.so) 
 
 
 ## Installation
@@ -96,16 +96,16 @@ python -m qai_hub_models.models.unet_segmentation.export
 Profile Job summary of Unet-Segmentation
 --------------------------------------------------
 Device: Samsung Galaxy S24 (14)
-Estimated Inference Time: 118.83 ms
-Estimated Peak Memory Range: 5.95-328.15 MB
+Estimated Inference Time: 113.23 ms
+Estimated Peak Memory Range: 4.46-345.06 MB
 Compute Units: NPU (31) | Total (31)
 
 Profile Job summary of Unet-Segmentation
 --------------------------------------------------
 Device: Samsung Galaxy S24 (14)
-Estimated Inference Time: 110.46 ms
-Estimated Peak Memory Range: 313.75-401.00 MB
-Compute Units: NPU (52) | Total (52)
+Estimated Inference Time: 110.49 ms
+Estimated Peak Memory Range: 9.41-107.93 MB
+Compute Units: NPU (51) | Total (51)
 
 
 ```