diff --git a/python/llm/src/ipex_llm/transformers/models/minicpmv.py b/python/llm/src/ipex_llm/transformers/models/minicpmv.py
index 340285ed193..bdf9aa3a535 100644
--- a/python/llm/src/ipex_llm/transformers/models/minicpmv.py
+++ b/python/llm/src/ipex_llm/transformers/models/minicpmv.py
@@ -15,6 +15,30 @@
 #
 
 
+import torch
+from transformers.generation.logits_process import RepetitionPenaltyLogitsProcessor
+
+
+# todo
+def patched_repetition_penalty_call(self, input_ids: torch.LongTensor, scores: torch.FloatTensor):
+    score = torch.gather(scores, 1, input_ids)
+
+    # if score < 0 then repetition penalty has to be
+    # multiplied to reduce the token probabilities
+    score = torch.where(score < 0, score * self.penalty, score / self.penalty)
+
+    # ipex llm changes start: call scatter on CPU
+    device = scores.device
+    scores = scores.to('cpu')
+    input_ids = input_ids.to('cpu')
+    score = score.to('cpu')
+    scores.scatter_(1, input_ids, score)
+    scores = scores.to(device)
+    # ipex llm changes end
+
+    return scores
+
+
 def minicpmv_generate_wrapper(origin_generate):
     def generate(
         self,
@@ -30,8 +54,7 @@ def generate(
         decode_text=False,
         **kwargs
     ):
-        if kwargs.get("repetition_penalty", None) is not None:
-            kwargs["repetition_penalty"] = 1
+        RepetitionPenaltyLogitsProcessor.__call__ = patched_repetition_penalty_call
         return origin_generate(
             self=self,
             input_ids=input_ids,