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README.md

@@ -36,8 +36,8 @@ 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 | 600.006 ms | 75 - 508 MB | FP16 | GPU |  [WhisperEncoder.tflite](https://huggingface.co/qualcomm/Whisper-Small-En/blob/main/WhisperEncoder.tflite) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 45.614 ms | 16 - 19 MB | FP16 | NPU |  [WhisperDecoder.tflite](https://huggingface.co/qualcomm/Whisper-Small-En/blob/main/WhisperDecoder.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 615.6 ms | 0 - 428 MB | FP16 | GPU |  [WhisperEncoder.tflite](https://huggingface.co/qualcomm/Whisper-Small-En/blob/main/WhisperEncoder.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 26.229 ms | 15 - 19 MB | FP16 | NPU |  [WhisperDecoder.tflite](https://huggingface.co/qualcomm/Whisper-Small-En/blob/main/WhisperDecoder.tflite) 
 
 
 ## Installation
@@ -95,23 +95,6 @@ device. This script does the following:
 python -m qai_hub_models.models.whisper_small_en.export
 ```
 
-```
-Profile Job summary of WhisperEncoder
---------------------------------------------------
-Device: QCS8550 (Proxy) (12)
-Estimated Inference Time: 602.37 ms
-Estimated Peak Memory Range: 69.53-498.63 MB
-Compute Units: GPU (585) | Total (585)
-
-Profile Job summary of WhisperDecoder
---------------------------------------------------
-Device: QCS8550 (Proxy) (12)
-Estimated Inference Time: 45.96 ms
-Estimated Peak Memory Range: 16.05-18.65 MB
-Compute Units: NPU (879),CPU (2) | Total (881)
-
-
-```
 ## How does this work?
 
 This [export script](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/Whisper-Small-En/export.py)