diff --git a/_posts/2024-10-25-intel-gpu-support-pytorch-2-5.md b/_posts/2024-10-25-intel-gpu-support-pytorch-2-5.md
index da8b907b5c69..6884f3e4f48f 100644
--- a/_posts/2024-10-25-intel-gpu-support-pytorch-2-5.md
+++ b/_posts/2024-10-25-intel-gpu-support-pytorch-2-5.md
@@ -1,7 +1,7 @@
 ---
 layout: blog_detail
 title: "Intel GPU Support Now Available in PyTorch 2.5"
-author: PyTorch Team at Intel
+author: PyTorch Team at Intel 
 ---
 
 Support for Intel GPUs is now available in PyTorch® 2.5, providing improved functionality and performance for Intel GPUs which including [Intel® Arc™ discrete graphics](https://www.intel.com/content/www/us/en/products/details/discrete-gpus/arc.html), [Intel® Core™ Ultra processors](https://www.intel.com/content/www/us/en/products/details/processors/core-ultra.html) with built-in Intel® Arc™ graphics and [Intel® Data Center GPU Max Series](https://www.intel.com/content/www/us/en/products/details/discrete-gpus/data-center-gpu/max-series.html). This integration brings Intel GPUs and the SYCL\* software stack into the official PyTorch stack, ensuring a consistent user experience and enabling more extensive AI application scenarios, particularly in the AI PC domain.
@@ -56,11 +56,11 @@ The performance of Intel GPU on PyTorch was continuously optimized to achieve de
 
 The latest performance data measured on top of PyTorch Dynamo Benchmarking Suite using Intel® Data Center GPU Max Series 1100 single card showcase the FP16/BF16 significant speedup ratio over FP32 on eager mode in Figure 1, and Torch.compile mode speedup ratio over eager mode in Figure 2\. Both inference and training reached the similar significant improvements. 
 
-![Figure 2: FP16/BF16 Performance Gains Over FP32 Eager](/assets/images/performance-gains-over-fp32-eager.png){:style="width:100%"}
+![Figure 2: FP16/BF16 Performance Gains Over FP32 Eager](/assets/images/performance-gains-over-fp32-eager-2.png){:style="width:100%"}
 
 Figure 2: FP16/BF16 Performance Gains Over FP32 Eager
 
-![Figure 3: Torch.compile Performance Gains Over Eager Mode](/assets/images/performance-gains-over-fp32-eager-2.png){:style="width:100%"}
+![Figure 3: Torch.compile Performance Gains Over Eager Mode](/assets/images/performance-gains-over-fp32-eager.png){:style="width:100%"}
 
 Figure 3: Torch.compile Performance Gains Over Eager Mode
 
diff --git a/assets/images/performance-gains-over-fp32-eager-2.png b/assets/images/performance-gains-over-fp32-eager-2.png
index d8d9c32f3edc..769b74fd9980 100644
Binary files a/assets/images/performance-gains-over-fp32-eager-2.png and b/assets/images/performance-gains-over-fp32-eager-2.png differ