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README.md

@@ -33,7 +33,7 @@ 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 | 51.073 ms | 9 - 13 MB | FP16 | NPU |  [FastSam-X.tflite](https://huggingface.co/qualcomm/FastSam-X/blob/main/FastSam-X.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 50.012 ms | 9 - 13 MB | FP16 | NPU |  [FastSam-X.tflite](https://huggingface.co/qualcomm/FastSam-X/blob/main/FastSam-X.tflite) 
 
 
 ## Installation
@@ -91,16 +91,6 @@ device. This script does the following:
 python -m qai_hub_models.models.fastsam_x.export
 ```
 
-```
-Profile Job summary of FastSam-X
---------------------------------------------------
-Device: Samsung Galaxy S24 (14)
-Estimated Inference Time: 36.14 ms
-Estimated Peak Memory Range: 0.09-135.60 MB
-Compute Units: NPU (420) | Total (420)
-
-
-```
 ## How does this work?
 
 This [export script](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/FastSam-X/export.py)