diff --git a/python/llm/example/GPU/HuggingFace/LLM/codellama/generate.py b/python/llm/example/GPU/HuggingFace/LLM/codellama/generate.py
index c772d8c2..05b14c2f 100644
--- a/python/llm/example/GPU/HuggingFace/LLM/codellama/generate.py
+++ b/python/llm/example/GPU/HuggingFace/LLM/codellama/generate.py
@@ -47,7 +47,7 @@ if __name__ == '__main__':
                                                  optimize_model=False,
                                                  trust_remote_code=True,
                                                  use_cache=True)
-    model = model.to('xpu')
+    model = model.half().to('xpu')
 
     # Load tokenizer
     tokenizer = CodeLlamaTokenizer.from_pretrained(model_path,
diff --git a/python/llm/example/GPU/HuggingFace/LLM/internlm/generate.py b/python/llm/example/GPU/HuggingFace/LLM/internlm/generate.py
index 7c3b2dac..d08fca0a 100644
--- a/python/llm/example/GPU/HuggingFace/LLM/internlm/generate.py
+++ b/python/llm/example/GPU/HuggingFace/LLM/internlm/generate.py
@@ -47,7 +47,7 @@ if __name__ == '__main__':
                                                  optimize_model=False,
                                                  trust_remote_code=True,
                                                  use_cache=True)
-    model = model.to('xpu')
+    model = model.half().to('xpu')
 
     # Load tokenizer
     tokenizer = AutoTokenizer.from_pretrained(model_path,
diff --git a/python/llm/example/GPU/HuggingFace/LLM/solar/generate.py b/python/llm/example/GPU/HuggingFace/LLM/solar/generate.py
index eb5e4aa4..25b692ca 100644
--- a/python/llm/example/GPU/HuggingFace/LLM/solar/generate.py
+++ b/python/llm/example/GPU/HuggingFace/LLM/solar/generate.py
@@ -47,7 +47,7 @@ if __name__ == '__main__':
                                                  load_in_4bit=True,
                                                  trust_remote_code=True,
                                                  use_cache=True)
-    model = model.to('xpu')
+    model = model.half().to('xpu')
 
     # Load tokenizer
     tokenizer = AutoTokenizer.from_pretrained(model_path,
diff --git a/python/llm/example/GPU/PyTorch-Models/Model/codellama/generate.py b/python/llm/example/GPU/PyTorch-Models/Model/codellama/generate.py
index d676666b..04af3a02 100644
--- a/python/llm/example/GPU/PyTorch-Models/Model/codellama/generate.py
+++ b/python/llm/example/GPU/PyTorch-Models/Model/codellama/generate.py
@@ -50,7 +50,7 @@ if __name__ == '__main__':
     # This will allow the memory-intensive embedding layer to utilize the CPU instead of iGPU.
     model = optimize_model(model)
 
-    model = model.to('xpu')
+    model = model.half().to('xpu')
 
     # Load tokenizer
     tokenizer = CodeLlamaTokenizer.from_pretrained(model_path, trust_remote_code=True)
diff --git a/python/llm/example/GPU/PyTorch-Models/Model/internlm2/generate.py b/python/llm/example/GPU/PyTorch-Models/Model/internlm2/generate.py
index 51690317..e8098e49 100644
--- a/python/llm/example/GPU/PyTorch-Models/Model/internlm2/generate.py
+++ b/python/llm/example/GPU/PyTorch-Models/Model/internlm2/generate.py
@@ -46,7 +46,7 @@ if __name__ == '__main__':
                                                  use_cache=True)
     model = optimize_model(model)
     
-    model = model.to('xpu')
+    model = model.half().to('xpu')
 
     # Load tokenizer
     tokenizer = AutoTokenizer.from_pretrained(model_path,
diff --git a/python/llm/example/GPU/PyTorch-Models/Model/mistral/generate.py b/python/llm/example/GPU/PyTorch-Models/Model/mistral/generate.py
index 0e717730..377e3156 100644
--- a/python/llm/example/GPU/PyTorch-Models/Model/mistral/generate.py
+++ b/python/llm/example/GPU/PyTorch-Models/Model/mistral/generate.py
@@ -49,7 +49,7 @@ if __name__ == '__main__':
     # This will allow the memory-intensive embedding layer to utilize the CPU instead of iGPU.
     model = optimize_model(model)
 
-    model = model.to('xpu')
+    model = model.half().to('xpu')
 
     # Load tokenizer
     tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
diff --git a/python/llm/example/GPU/PyTorch-Models/Model/solar/generate.py b/python/llm/example/GPU/PyTorch-Models/Model/solar/generate.py
index b612bc2f..b328b51e 100644
--- a/python/llm/example/GPU/PyTorch-Models/Model/solar/generate.py
+++ b/python/llm/example/GPU/PyTorch-Models/Model/solar/generate.py
@@ -49,7 +49,7 @@ if __name__ == '__main__':
     # When running LLMs on Intel iGPUs for Windows users, we recommend setting `cpu_embedding=True` in the optimize_model function.
     # This will allow the memory-intensive embedding layer to utilize the CPU instead of iGPU.
     model = optimize_model(model)
-    model = model.to('xpu')
+    model = model.half().to('xpu')
 
     # Load tokenizer
     tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)