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README.md

@@ -33,7 +33,8 @@ 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 | 47.957 ms | 4 - 23 MB | FP16 | NPU |  [SAMDecoder.tflite](https://huggingface.co/qualcomm/Segment-Anything-Model/blob/main/SAMDecoder.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 48.417 ms | 4 - 13 MB | FP16 | NPU |  [SAMDecoder.tflite](https://huggingface.co/qualcomm/Segment-Anything-Model/blob/main/SAMDecoder.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 12002.934 ms | 2618 - 2622 MB | FP32 | CPU |  [SAMEncoder.tflite](https://huggingface.co/qualcomm/Segment-Anything-Model/blob/main/SAMEncoder.tflite) 
 
 
 ## Installation
@@ -91,16 +92,6 @@ device. This script does the following:
 python -m qai_hub_models.models.sam.export
 ```
 
-```
-Profile Job summary of SAMDecoder
---------------------------------------------------
-Device: QCS8550 (Proxy) (12)
-Estimated Inference Time: 48.30 ms
-Estimated Peak Memory Range: 3.79-11.81 MB
-Compute Units: NPU (340) | Total (340)
-
-
-```
 ## How does this work?
 
 This [export script](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/Segment-Anything-Model/export.py)