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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 | 0.633 ms | 0 - 72 MB | INT8 | NPU |  [Shufflenet-v2Quantized.tflite](https://huggingface.co/qualcomm/Shufflenet-v2Quantized/blob/main/Shufflenet-v2Quantized.tflite) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 0.591 ms | 0 - 63 MB | INT8 | NPU |  [Shufflenet-v2Quantized.so](https://huggingface.co/qualcomm/Shufflenet-v2Quantized/blob/main/Shufflenet-v2Quantized.so) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 0.606 ms | 0 - 63 MB | INT8 | NPU |  [Shufflenet-v2Quantized.tflite](https://huggingface.co/qualcomm/Shufflenet-v2Quantized/blob/main/Shufflenet-v2Quantized.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 0.586 ms | 0 - 4 MB | INT8 | NPU |  [Shufflenet-v2Quantized.so](https://huggingface.co/qualcomm/Shufflenet-v2Quantized/blob/main/Shufflenet-v2Quantized.so) 
 
 
 
@@ -102,8 +102,8 @@ python -m qai_hub_models.models.shufflenet_v2_quantized.export
 Profile Job summary of Shufflenet-v2Quantized
 --------------------------------------------------
 Device: Snapdragon X Elite CRD (11)
-Estimated Inference Time: 0.66 ms
-Estimated Peak Memory Range: 0.48-0.48 MB
+Estimated Inference Time: 0.76 ms
+Estimated Peak Memory Range: 0.51-0.51 MB
 Compute Units: NPU (122) | Total (122)