diff --git a/python/llm/src/ipex_llm/transformers/convert.py b/python/llm/src/ipex_llm/transformers/convert.py
index e3674c6c..05ac94a4 100644
--- a/python/llm/src/ipex_llm/transformers/convert.py
+++ b/python/llm/src/ipex_llm/transformers/convert.py
@@ -1049,6 +1049,10 @@ def _optimize_pre(model, qtype=None):
             model.llm.config.model_type = "qwen2"
         elif model.config.hidden_size == 4096 and model.config.vocab_size == 128256:
             model.llm.config.model_type = "llama"
+        elif model.config.hidden_size == 1536 and model.config.vocab_size == 73464:
+            from ipex_llm.transformers.models.minicpm3 import pre_compute_inv_freq
+            model.llm.apply(pre_compute_inv_freq)
+            model.llm.config.model_type = "minicpm"
         _optimize_pre(model.llm, qtype=qtype)
         model.llm.config.model_type = "minicpmv"
     elif model.config.model_type == "chatglm":
@@ -2137,6 +2141,9 @@ def _optimize_post(model, lightweight_bmm=False):
         elif model.config.hidden_size == 4096 and model.config.vocab_size == 128256:
             # MiniCPM-V 2.5
             model.llm.config.model_type = "llama"
+        elif model.config.hidden_size == 1536 and model.config.vocab_size == 73464:
+            # MiniCPM-V ?
+            model.llm.config.model_type = "minicpm"
         _optimize_post(model.llm, lightweight_bmm=lightweight_bmm)
         model.llm.config.model_type = "minicpmv"
 
diff --git a/python/llm/src/ipex_llm/transformers/models/minicpm.py b/python/llm/src/ipex_llm/transformers/models/minicpm.py
index 6e2cab0f..30a26277 100644
--- a/python/llm/src/ipex_llm/transformers/models/minicpm.py
+++ b/python/llm/src/ipex_llm/transformers/models/minicpm.py
@@ -100,8 +100,15 @@ def minicpm_attention_forward(
         kv_seq_len += past_key_value.get_usable_length(kv_seq_len, self.layer_idx)
 
     if should_use_fuse_rope(hidden_states, position_ids, self.training):
+        if self.rotary_emb.__class__.__name__ == "MiniCPMLongRoPE":
+            if kv_seq_len > self.rotary_emb.original_max_position_embeddings:
+                inv_freq = self.rotary_emb.long_inv_freq
+            else:
+                inv_freq = self.rotary_emb.short_inv_freq
+        else:
+            inv_freq = self.rotary_emb.inv_freq
         import xe_addons
-        xe_addons.rotary_half_inplaced(self.rotary_emb.inv_freq, position_ids,
+        xe_addons.rotary_half_inplaced(inv_freq, position_ids,
                                        query_states, key_states)
     else:
         cos, sin = self.rotary_emb(value_states.to(torch.float32), seq_len=kv_seq_len)