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README.md

@@ -36,9 +36,9 @@ 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 | QNN Binary | 11.362 ms | 0 - 42 MB | UINT16 | NPU |  [TextEncoder_Quantized.bin](https://huggingface.co/qualcomm/Stable-Diffusion/blob/main/TextEncoder_Quantized.bin) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Binary | 393.878 ms | 0 - 11 MB | UINT16 | NPU |  [VAEDecoder_Quantized.bin](https://huggingface.co/qualcomm/Stable-Diffusion/blob/main/VAEDecoder_Quantized.bin) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Binary | 256.698 ms | 0 - 12 MB | UINT16 | NPU |  [UNet_Quantized.bin](https://huggingface.co/qualcomm/Stable-Diffusion/blob/main/UNet_Quantized.bin) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Binary | 11.371 ms | 0 - 31 MB | UINT16 | NPU |  [TextEncoder_Quantized.bin](https://huggingface.co/qualcomm/Stable-Diffusion/blob/main/TextEncoder_Quantized.bin) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Binary | 255.354 ms | 0 - 45 MB | UINT16 | NPU |  [UNet_Quantized.bin](https://huggingface.co/qualcomm/Stable-Diffusion/blob/main/UNet_Quantized.bin) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Binary | 392.074 ms | 0 - 25 MB | UINT16 | NPU |  [VAEDecoder_Quantized.bin](https://huggingface.co/qualcomm/Stable-Diffusion/blob/main/VAEDecoder_Quantized.bin) 
 
 
 ## Installation
@@ -99,25 +99,25 @@ python -m qai_hub_models.models.stable_diffusion_quantized.export
 ```
 Profile Job summary of TextEncoder_Quantized
 --------------------------------------------------
-Device: Samsung Galaxy S23 (13)
-Estimated Inference Time: 11.36 ms
-Estimated Peak Memory Range: 0.05-42.00 MB
+Device: Samsung Galaxy S24 (14)
+Estimated Inference Time: 8.08 ms
+Estimated Peak Memory Range: 0.01-137.09 MB
 Compute Units: NPU (570) | Total (570)
 
-Profile Job summary of VAEDecoder_Quantized
---------------------------------------------------
-Device: Samsung Galaxy S23 (13)
-Estimated Inference Time: 393.88 ms
-Estimated Peak Memory Range: 0.21-11.15 MB
-Compute Units: NPU (409) | Total (409)
-
 Profile Job summary of UNet_Quantized
 --------------------------------------------------
-Device: Samsung Galaxy S23 (13)
-Estimated Inference Time: 256.70 ms
-Estimated Peak Memory Range: 0.14-12.25 MB
+Device: Samsung Galaxy S24 (14)
+Estimated Inference Time: 188.59 ms
+Estimated Peak Memory Range: 0.34-1242.36 MB
 Compute Units: NPU (5421) | Total (5421)
 
+Profile Job summary of VAEDecoder_Quantized
+--------------------------------------------------
+Device: Samsung Galaxy S24 (14)
+Estimated Inference Time: 295.06 ms
+Estimated Peak Memory Range: 0.18-87.59 MB
+Compute Units: NPU (409) | Total (409)
+
 
 ```
 ## How does this work?
@@ -229,7 +229,7 @@ Explore all available models on [Qualcomm® AI Hub](https://aihub.qualcomm.com/)
 ## License
 - The license for the original implementation of Stable-Diffusion can be found
   [here](https://github.com/CompVis/stable-diffusion/blob/main/LICENSE).
-- The license for the compiled assets for on-device deployment can be found [here](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/Qualcomm+AI+Hub+Proprietary+License.pdf).
+- The license for the compiled assets for on-device deployment can be found [here]({deploy_license_url})
 
 ## References
 * [High-Resolution Image Synthesis with Latent Diffusion Models](https://arxiv.org/abs/2112.10752)