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README.md

@@ -38,8 +38,8 @@ 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 | 3.325 ms | 0 - 2 MB | INT8 | NPU |  [DeepLabV3-Plus-MobileNet-Quantized.tflite](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet-Quantized/blob/main/DeepLabV3-Plus-MobileNet-Quantized.tflite) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 5.342 ms | 0 - 12 MB | INT8 | NPU |  [DeepLabV3-Plus-MobileNet-Quantized.so](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet-Quantized/blob/main/DeepLabV3-Plus-MobileNet-Quantized.so) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 3.321 ms | 0 - 17 MB | INT8 | NPU |  [DeepLabV3-Plus-MobileNet-Quantized.tflite](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet-Quantized/blob/main/DeepLabV3-Plus-MobileNet-Quantized.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 5.185 ms | 0 - 14 MB | INT8 | NPU |  [DeepLabV3-Plus-MobileNet-Quantized.so](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet-Quantized/blob/main/DeepLabV3-Plus-MobileNet-Quantized.so) 
 
 
 
@@ -101,10 +101,10 @@ python -m qai_hub_models.models.deeplabv3_plus_mobilenet_quantized.export
 ```
 Profile Job summary of DeepLabV3-Plus-MobileNet-Quantized
 --------------------------------------------------
-Device: SA8255 (Proxy) (13)
-Estimated Inference Time: 5.33 ms
-Estimated Peak Memory Range: 0.77-13.24 MB
-Compute Units: NPU (100) | Total (100)
+Device: Snapdragon X Elite CRD (11)
+Estimated Inference Time: 4.36 ms
+Estimated Peak Memory Range: 0.77-0.77 MB
+Compute Units: NPU (99) | Total (99)
 
 
 ```