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README.md

@@ -37,7 +37,7 @@ 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 | 8.341 ms | 1 - 2 MB | INT8 | NPU |  [FFNet-78S-Quantized.tflite](https://huggingface.co/qualcomm/FFNet-78S-Quantized/blob/main/FFNet-78S-Quantized.tflite) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 5.952 ms | 8 - 26 MB | INT8 | NPU |  [FFNet-78S-Quantized.so](https://huggingface.co/qualcomm/FFNet-78S-Quantized/blob/main/FFNet-78S-Quantized.so) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 5.979 ms | 6 - 18 MB | INT8 | NPU |  [FFNet-78S-Quantized.so](https://huggingface.co/qualcomm/FFNet-78S-Quantized/blob/main/FFNet-78S-Quantized.so) 
 
 
 ## Installation
@@ -99,7 +99,7 @@ python -m qai_hub_models.models.ffnet_78s_quantized.export
 Profile Job summary of FFNet-78S-Quantized
 --------------------------------------------------
 Device: Snapdragon X Elite CRD (11)
-Estimated Inference Time: 7.10 ms
+Estimated Inference Time: 7.09 ms
 Estimated Peak Memory Range: 6.01-6.01 MB
 Compute Units: NPU (146) | Total (146)