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README.md

@@ -39,8 +39,8 @@ 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 | 1.816 ms | 0 - 3 MB | INT8 | NPU |  [WideResNet50-Quantized.tflite](https://huggingface.co/qualcomm/WideResNet50-Quantized/blob/main/WideResNet50-Quantized.tflite) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 2.041 ms | 0 - 139 MB | INT8 | NPU |  [WideResNet50-Quantized.so](https://huggingface.co/qualcomm/WideResNet50-Quantized/blob/main/WideResNet50-Quantized.so) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 1.776 ms | 0 - 2 MB | INT8 | NPU |  [WideResNet50-Quantized.tflite](https://huggingface.co/qualcomm/WideResNet50-Quantized/blob/main/WideResNet50-Quantized.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 2.031 ms | 0 - 361 MB | INT8 | NPU |  [WideResNet50-Quantized.so](https://huggingface.co/qualcomm/WideResNet50-Quantized/blob/main/WideResNet50-Quantized.so) 
 
 
 
@@ -103,8 +103,8 @@ python -m qai_hub_models.models.wideresnet50_quantized.export
 Profile Job summary of WideResNet50-Quantized
 --------------------------------------------------
 Device: SA8255 (Proxy) (13)
-Estimated Inference Time: 2.04 ms
-Estimated Peak Memory Range: 0.01-128.10 MB
+Estimated Inference Time: 2.03 ms
+Estimated Peak Memory Range: 0.01-413.72 MB
 Compute Units: NPU (78) | Total (78)