diff --git a/python/llm/src/ipex_llm/transformers/models/llama.py b/python/llm/src/ipex_llm/transformers/models/llama.py
index 85f58f61..fd7ecffd 100644
--- a/python/llm/src/ipex_llm/transformers/models/llama.py
+++ b/python/llm/src/ipex_llm/transformers/models/llama.py
@@ -1497,6 +1497,13 @@ def llama_attention_forward_4_41_original(
                                                      value_states.to(device, dtype=torch.float16),
                                                      is_causal=True)
         attn_weights = None
+    elif use_sdp_causal(q_len, kv_seq_len, self.head_dim,
+                        query_states, self.training):
+        import xe_addons
+        attn_output = xe_addons.sdp_causal(query_states, key_states.contiguous(),
+                                           value_states.contiguous(), new_attention_mask)
+        attn_output = attn_output.view(query_states.shape)
+        attn_weights = None
     elif not self.training and not hidden_states.requires_grad and \
             use_sdp(q_len, key_states.shape[2], self.head_dim, query_states):
         import xe_addons
@@ -2040,6 +2047,13 @@ def llama_attention_forward_4_38_original(
                                                      value_states.to(device, dtype=torch.float16),
                                                      is_causal=True)
         attn_weights = None
+    elif use_sdp_causal(q_len, kv_seq_len, self.head_dim,
+                        query_states, self.training):
+        import xe_addons
+        attn_output = xe_addons.sdp_causal(query_states, key_states.contiguous(),
+                                           value_states.contiguous(), new_attention_mask)
+        attn_output = attn_output.view(query_states.shape)
+        attn_weights = None
     elif not self.training and not hidden_states.requires_grad and \
             use_sdp(q_len, key_states.shape[2], self.head_dim, query_states):
         import xe_addons