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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 | 13.206 ms | 20 - 35 MB | FP16 | NPU |  [DeepLabV3-Plus-MobileNet.tflite](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet/blob/main/DeepLabV3-Plus-MobileNet.tflite) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 12.804 ms | 2 - 19 MB | FP16 | NPU |  [DeepLabV3-Plus-MobileNet.so](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet/blob/main/DeepLabV3-Plus-MobileNet.so) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 13.09 ms | 20 - 21 MB | FP16 | NPU |  [DeepLabV3-Plus-MobileNet.tflite](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet/blob/main/DeepLabV3-Plus-MobileNet.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 12.915 ms | 2 - 18 MB | FP16 | NPU |  [DeepLabV3-Plus-MobileNet.so](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet/blob/main/DeepLabV3-Plus-MobileNet.so) 
 
 
 ## Installation
@@ -95,16 +95,9 @@ python -m qai_hub_models.models.deeplabv3_plus_mobilenet.export
 ```
 Profile Job summary of DeepLabV3-Plus-MobileNet
 --------------------------------------------------
-Device: QCS8550 (Proxy) (12)
-Estimated Inference Time: 13.24 ms
-Estimated Peak Memory Range: 21.14-23.32 MB
-Compute Units: NPU (98) | Total (98)
-
-Profile Job summary of DeepLabV3-Plus-MobileNet
---------------------------------------------------
-Device: QCS8550 (Proxy) (12)
-Estimated Inference Time: 12.99 ms
-Estimated Peak Memory Range: 3.05-25.23 MB
+Device: Snapdragon X Elite CRD (11)
+Estimated Inference Time: 16.53 ms
+Estimated Peak Memory Range: 3.02-3.02 MB
 Compute Units: NPU (124) | Total (124)