diff --git a/optimum/habana/transformers/models/mllama/modeling_mllama.py b/optimum/habana/transformers/models/mllama/modeling_mllama.py
index 28a61d590..7f09fccac 100644
--- a/optimum/habana/transformers/models/mllama/modeling_mllama.py
+++ b/optimum/habana/transformers/models/mllama/modeling_mllama.py
@@ -777,10 +777,15 @@ def forward(
             if cache_position is not None:
                 cross_attention_mask = cross_attention_mask[:, :, cache_position]
                 full_text_row_masked_out_mask = full_text_row_masked_out_mask[:, :, cache_position]
-            elif token_idx is not None and past_key_values is not None:
-                cross_attention_mask = torch.index_select(cross_attention_mask, -2, token_idx - 1)
-                full_text_row_masked_out_mask = torch.index_select(full_text_row_masked_out_mask, -2, token_idx - 1)
-
+            elif past_key_values is not None:
+                if token_idx is not None:
+                    cross_attention_mask = torch.index_select(cross_attention_mask, -2, token_idx - 1)
+                    full_text_row_masked_out_mask = torch.index_select(
+                        full_text_row_masked_out_mask, -2, token_idx - 1
+                    )
+                else:
+                    cross_attention_mask = cross_attention_mask[:, :, -1:]
+                    full_text_row_masked_out_mask = full_text_row_masked_out_mask[:, :, -1:]
         outputs = self.language_model(
             input_ids=input_ids,
             attention_mask=attention_mask,
@@ -895,7 +900,7 @@ def _update_model_kwargs_for_generation(self, outputs, model_kwargs, is_encoder_
             - add token_idx handling
         """
         cross_attention_mask_prev = model_kwargs.get("cross_attention_mask", None)
-        model_kwargs = super()._update_model_kwargs_for_generation(
+        model_kwargs = super(MllamaForConditionalGeneration, self)._update_model_kwargs_for_generation(
             outputs=outputs,
             model_kwargs=model_kwargs,
             is_encoder_decoder=is_encoder_decoder,
@@ -909,6 +914,10 @@ def _update_model_kwargs_for_generation(self, outputs, model_kwargs, is_encoder_
                 mask = cross_attention_mask_prev[:, token_idx - 2 : token_idx - 1, ...]
                 cross_attention_mask_prev.index_copy_(1, token_idx - 1, mask)
                 model_kwargs["cross_attention_mask"] = cross_attention_mask_prev
+            else:
+                model_kwargs["cross_attention_mask"] = torch.cat(
+                    [cross_attention_mask_prev, cross_attention_mask_prev[:, -1:, ...]], dim=1
+                )
         return model_kwargs