diff --git a/fastdeploy/model_executor/layers/attention/append_attn_backend.py b/fastdeploy/model_executor/layers/attention/append_attn_backend.py
index ddebd15d41..a638ac33c7 100644
--- a/fastdeploy/model_executor/layers/attention/append_attn_backend.py
+++ b/fastdeploy/model_executor/layers/attention/append_attn_backend.py
@@ -140,8 +140,6 @@ class AppendAttentionBackend(AttentionBackend):
         self.rope_3d: bool = getattr(fd_config.model_config, "rope_3d", False) or getattr(
             fd_config.model_config, "use_3d_rope", False
         )
-        if fd_config.speculative_config.model_type != "main":
-            self.rope_3d = False
         self.causal: bool = getattr(fd_config.model_config, "causal", True)
         self.speculative_method: str = fd_config.speculative_config.method
         self.speculate_max_draft_token_num: int = fd_config.speculative_config.num_speculative_tokens
diff --git a/fastdeploy/worker/input_batch.py b/fastdeploy/worker/input_batch.py
index 92d03f2071..9071453ab9 100644
--- a/fastdeploy/worker/input_batch.py
+++ b/fastdeploy/worker/input_batch.py
@@ -709,15 +709,7 @@ class ProposerInputBatch(InputBatch):
             dtype="bfloat16",
         )
 
-        tmp_position_ids = paddle.arange(self.model_config.max_model_len).reshape((1, -1))
-
-        self.rope_emb = get_rope(
-            rotary_dim=self.model_config.head_dim,
-            position_ids=tmp_position_ids,
-            base=self.model_config.rope_theta,
-            model_config=self.model_config,
-            partial_rotary_factor=self.model_config.partial_rotary_factor,
-        )
+        self.rope_emb = paddle.clone(self.target_model_input_batch["rope_emb"])
 
         # self.caches = self.cache_kvs
         # Inherit generation hyperparameters from the main model for consistency
@@ -915,14 +907,35 @@ class ProposerInputBatch(InputBatch):
             fill_paddle_tensor(self, "target_hidden_states", 0)
 
             # Reset rope embedding by recreating with default position_ids
-            tmp_position_ids = paddle.arange(self.model_config.max_model_len).reshape((1, -1))
-            self.rope_emb = get_rope(
-                rotary_dim=self.model_config.head_dim,
-                position_ids=tmp_position_ids,
-                base=self.model_config.rope_theta,
-                model_config=self.model_config,
-                partial_rotary_factor=self.model_config.partial_rotary_factor,
-            )
+            if self.enable_mm:
+                head_dim = self.model_config.head_dim
+                if "qwen" in self.model_config.model_type or "paddleocr" in self.model_config.model_type:
+                    rope_head_dim = head_dim
+                else:
+                    rope_head_dim = head_dim // 2
+
+                self.rope_emb = paddle.full(
+                    shape=[
+                        self.scheduler_config.max_num_seqs,
+                        2,
+                        1,
+                        self.model_config.max_model_len,
+                        1,
+                        rope_head_dim,
+                    ],
+                    fill_value=0,
+                    dtype="float32",
+                )
+                self.image_features = None
+                self.image_features_list = None
+            else:
+                self.rope_emb = get_rope(
+                    rotary_dim=self.model_config.head_dim,
+                    position_ids=paddle.arange(self.model_config.max_model_len).reshape((1, -1)),
+                    base=self.model_config.rope_theta,
+                    model_config=self.model_config,
+                    partial_rotary_factor=self.model_config.partial_rotary_factor,
+                )
 
             # Reset generation hyperparameters from the main model
             self.top_p = self.target_model_input_batch["top_p"]
diff --git a/tests/spec_decode/test_mtp_proposer.py b/tests/spec_decode/test_mtp_proposer.py
index 6679ce4286..ca7758f659 100644
--- a/tests/spec_decode/test_mtp_proposer.py
+++ b/tests/spec_decode/test_mtp_proposer.py
@@ -22,6 +22,7 @@ from utils import FakeModelConfig, get_default_test_fd_config
 
 from fastdeploy.config import SpeculativeConfig
 from fastdeploy.engine.request import Request, RequestType
+from fastdeploy.model_executor.layers.rotary_embedding import get_rope
 from fastdeploy.spec_decode.mtp import MTPProposer
 
 
@@ -112,6 +113,30 @@ class TestMTPProposer(unittest.TestCase):
             "is_block_step": paddle.zeros([2], dtype="bool"),
             "actual_draft_token_num": paddle.zeros([2], dtype="int32"),
         }
+        self.update_model_inputs_rope()
+
+    def update_model_inputs_rope(self):
+        if self.fd_config.model_config.enable_mm:
+            self.target_model_inputs["rope_emb"] = paddle.full(
+                shape=[
+                    self.fd_config.scheduler_config.max_num_seqs,
+                    2,
+                    1,
+                    self.fd_config.model_config.max_model_len,
+                    1,
+                    self.fd_config.model_config.head_dim,
+                ],
+                fill_value=0,
+                dtype="float32",
+            )
+        else:
+            self.target_model_inputs["rope_emb"] = get_rope(
+                rotary_dim=self.fd_config.model_config.head_dim,
+                position_ids=paddle.arange(self.fd_config.model_config.max_model_len).reshape((1, -1)),
+                base=self.fd_config.model_config.rope_theta,
+                model_config=self.fd_config.model_config,
+                partial_rotary_factor=self.fd_config.model_config.partial_rotary_factor,
+            )
 
     @patch("fastdeploy.spec_decode.mtp.get_model_loader")
     @patch("fastdeploy.spec_decode.mtp.get_attention_backend")
@@ -604,6 +629,7 @@ class TestMTPProposer(unittest.TestCase):
         mock_rope.return_value = paddle.zeros([1, 2048, 64])
 
         self.fd_config.model_config.enable_mm = True
+        self.update_model_inputs_rope()
         proposer = MTPProposer(
             self.fd_config, self.main_model, self.local_rank, self.device_id, self.target_model_inputs
         )