diff --git a/fastdeploy/model_executor/models/glm4_mtp.py b/fastdeploy/model_executor/models/glm4_mtp.py
index d16632c2b4..c28023202d 100644
--- a/fastdeploy/model_executor/models/glm4_mtp.py
+++ b/fastdeploy/model_executor/models/glm4_mtp.py
@@ -28,8 +28,6 @@ from fastdeploy.model_executor.forward_meta import ForwardMeta
 from fastdeploy.model_executor.graph_optimization.decorator import (
     support_graph_optimization,
 )
-from fastdeploy.model_executor.layers.embeddings import VocabParallelEmbedding
-from fastdeploy.model_executor.layers.lm_head import ParallelLMHead
 from fastdeploy.model_executor.layers.mtp_linear import ParallelEHProjection
 from fastdeploy.model_executor.layers.normalization import RMSNorm
 from fastdeploy.model_executor.models.glm4_moe import Glm4MoeDecoderLayer
@@ -119,12 +117,8 @@ class SharedHead(nn.Module):
             eps=fd_config.model_config.rms_norm_eps,
             prefix=f"{prefix}.shared_head.norm",
         )
-        self.head = ParallelLMHead(
-            fd_config,
-            embedding_dim=fd_config.model_config.hidden_size,
-            num_embeddings=fd_config.model_config.vocab_size,
-            prefix=f"{prefix}.shared_head.head",
-        )
+        if fd_config.speculative_config.sharing_model is not None:
+            self.head = fd_config.speculative_config.sharing_model.lm_head
 
     def forward(self, hidden_states: paddle.Tensor) -> paddle.Tensor:
         # NOTE(wangyanpeng04): Just for compute logits
@@ -216,15 +210,8 @@ class Glm4MTPModel(nn.Layer):
 
         assert self.num_mtp_layers == 1, f"Currently only supports single MTP layer, but got {self.num_mtp_layers}"
 
-        self.embed_tokens = VocabParallelEmbedding(
-            fd_config=fd_config,
-            num_embeddings=fd_config.model_config.vocab_size,
-            embedding_dim=fd_config.model_config.hidden_size,
-            params_dtype=paddle.get_default_dtype(),
-            prefix=(
-                f"{fd_config.model_config.pretrained_config.prefix_name}.layers.{self.mtp_start_layer_idx}.embed_tokens"
-            ),
-        )
+        if fd_config.speculative_config.sharing_model is not None:
+            self.embed_tokens = fd_config.speculative_config.sharing_model.model.embed_tokens
 
         self.layers = nn.LayerDict(
             {
diff --git a/fastdeploy/rl/rollout_model.py b/fastdeploy/rl/rollout_model.py
index e4dd3ace5a..27c7b54236 100644
--- a/fastdeploy/rl/rollout_model.py
+++ b/fastdeploy/rl/rollout_model.py
@@ -18,8 +18,10 @@ import copy
 from typing import Dict
 
 import paddle
+import paddle.distributed as dist
 from paddle import nn
 
+from fastdeploy import envs
 from fastdeploy.config import FDConfig
 from fastdeploy.model_executor.model_loader import get_model_loader
 from fastdeploy.model_executor.models.ernie4_5_moe import (
@@ -34,6 +36,10 @@ from fastdeploy.model_executor.models.glm4_moe import (
     Glm4MoeForCausalLM,
     Glm4MoePretrainedModel,
 )
+from fastdeploy.model_executor.models.glm4_mtp import (
+    Glm4MTPForCausalLM,
+    Glm4MTPPretrainedModel,
+)
 from fastdeploy.model_executor.models.model_base import ModelRegistry
 from fastdeploy.model_executor.models.qwen2 import (
     Qwen2ForCausalLM,
@@ -698,12 +704,42 @@ class Glm4MoeForCausalLMRL(Glm4MoeForCausalLM, BaseRLModel):
             fd_config (FDConfig): Configurations for the LLM model.
         """
         super(Glm4MoeForCausalLMRL, self).__init__(fd_config)
+        self.num_nextn_predict_layers = fd_config.model_config.num_nextn_predict_layers
+
+        if self.num_nextn_predict_layers > 0:
+            fd_config.parallel_config.tp_group = None
+            fd_config.parallel_config.ep_group = None
+            self.mtp_fd_config = copy.deepcopy(fd_config)
+            fd_config.parallel_config.tp_group = dist.get_group(
+                fd_config.parallel_config.data_parallel_rank + envs.FD_TP_GROUP_GID_OFFSET
+            )
+            fd_config.parallel_config.ep_group = dist.get_group(
+                fd_config.parallel_config.data_parallel_size + envs.FD_TP_GROUP_GID_OFFSET
+            )
+            self.fd_config.parallel_config.tp_group = dist.get_group(
+                fd_config.parallel_config.data_parallel_rank + envs.FD_TP_GROUP_GID_OFFSET
+            )
+            self.fd_config.parallel_config.ep_group = dist.get_group(
+                fd_config.parallel_config.data_parallel_size + envs.FD_TP_GROUP_GID_OFFSET
+            )
+            self.update_mtp_config(self.mtp_fd_config)
+            self.mtp_layers = Glm4MTPForCausalLMRL(self.mtp_fd_config)
 
     @classmethod
     def name(self) -> str:
         """name"""
         return "Glm4MoeForCausalLMRL"
 
+    def update_mtp_config(self, mtp_fd_config):
+        mtp_fd_config.model_config.architectures[0] = mtp_fd_config.model_config.architectures[0].replace("Moe", "MTP")
+        mtp_fd_config.speculative_config.sharing_model = None
+        mtp_fd_config.model_config.start_layer_index = mtp_fd_config.model_config.num_hidden_layers
+        mtp_fd_config.model_config.num_hidden_layers = 1
+        mtp_fd_config.model_config.model = mtp_fd_config.speculative_config.model
+        if mtp_fd_config.speculative_config.quantization != "":
+            mtp_fd_config.model_config.quantization = mtp_fd_config.speculative_config.quantization
+        mtp_fd_config.speculative_config.model_type = "mtp"
+
     def get_name_mappings_to_training(self, trainer_degree=None) -> Dict[str, str]:
         """Generate mapping between inference and training parameter for RL(donot delete!)."""
         if self._mappings_built:
@@ -757,9 +793,106 @@ class Glm4MoeForCausalLMRL(Glm4MoeForCausalLM, BaseRLModel):
             _add_layer_mappings(layer_idx)
 
         self._complete_missing_mappings()
+
+        # extra for mtp
+        if self.num_nextn_predict_layers > 0:
+            mtp_infer_to_train_mapping = self.mtp_layers.get_name_mappings_to_training(trainer_degree)
+            self.infer_to_train_mapping.update(mtp_infer_to_train_mapping)
+
         infer_to_train_mapping_copy = copy.deepcopy(self.infer_to_train_mapping)
         for key in infer_to_train_mapping_copy.keys():
             if "mlp.experts.gate_correction_bias" in key:
                 self.infer_to_train_mapping.pop(key)
 
         return self.infer_to_train_mapping
+
+
+class Glm4MTPForCausalLMRL(Glm4MTPForCausalLM, BaseRLModel):
+    """
+    Glm4MTPForCausalLMRL
+    """
+
+    _get_tensor_parallel_mappings = Glm4MTPPretrainedModel._get_tensor_parallel_mappings
+
+    def __init__(self, fd_config: FDConfig):
+        """
+        Args:
+            fd_config (FDConfig): Configurations for the LLM model.
+        """
+        super(Glm4MTPForCausalLMRL, self).__init__(fd_config)
+
+    @classmethod
+    def name(self) -> str:
+        """name"""
+        return "Glm4MTPForCausalLMRL"
+
+    def get_name_mappings_to_training(self, trainer_degree=None) -> Dict[str, str]:
+        """Generate mapping between inference and training parameter for RL(donot delete!)."""
+        if self._mappings_built:
+            return self.infer_to_train_mapping
+
+        self.infer_to_train_mapping = {}
+        self._mappings_built = True
+
+        # Prepare placeholders
+        place_holders = ["weight"]
+
+        base_name = "model.layers"
+
+        # Helper function to add layer mappings
+        def _add_layer_mappings(layer_idx: int):
+            # MTP specific mappings
+            self.infer_to_train_mapping[f"{base_name}.{layer_idx}.shared_head.head.weight"] = (
+                f"{base_name}.{layer_idx}.shared_head.head.weight"
+            )
+            self.infer_to_train_mapping[f"{base_name}.{layer_idx}.shared_head.norm.weight"] = (
+                f"{base_name}.{layer_idx}.shared_head.norm.weight"
+            )
+            self.infer_to_train_mapping[f"{base_name}.{layer_idx}.eh_proj.weight"] = (
+                f"{base_name}.{layer_idx}.eh_proj.weight"
+            )
+            self.infer_to_train_mapping[f"{base_name}.{layer_idx}.enorm.weight"] = (
+                f"{base_name}.{layer_idx}.enorm.weight"
+            )
+            self.infer_to_train_mapping[f"{base_name}.{layer_idx}.hnorm.weight"] = (
+                f"{base_name}.{layer_idx}.hnorm.weight"
+            )
+
+            # MoE specific mappings
+            self.infer_to_train_mapping[f"{base_name}.{layer_idx}.mlp.gate.weight"] = (
+                f"{base_name}.{layer_idx}.mlp.gate.weight"
+            )
+
+            self.infer_to_train_mapping[f"{base_name}.{layer_idx}.mlp.gate.e_score_correction_bias"] = (
+                f"{base_name}.{layer_idx}.mlp.gate.e_score_correction_bias"
+            )
+
+            # MoE experts mappings
+            for expert_idx in range(self.fd_config.model_config.n_routed_experts):
+                for ph in place_holders:
+                    # up_gate_proj (up_gate_proj)
+                    up_gate_proj_key = f"{base_name}.{layer_idx}.mlp.experts.up_gate_proj_weight"
+                    if up_gate_proj_key not in self.infer_to_train_mapping:
+                        self.infer_to_train_mapping[up_gate_proj_key] = []
+                    self.infer_to_train_mapping[up_gate_proj_key].append(
+                        f"{base_name}.{layer_idx}.mlp.experts.{expert_idx}.up_gate_proj.{ph}"
+                    )
+
+                    # down_proj (down_proj)
+                    down_proj_key = f"{base_name}.{layer_idx}.mlp.experts.down_proj_weight"
+                    if down_proj_key not in self.infer_to_train_mapping:
+                        self.infer_to_train_mapping[down_proj_key] = []
+                    self.infer_to_train_mapping[down_proj_key].append(
+                        f"{base_name}.{layer_idx}.mlp.experts.{expert_idx}.down_proj.{ph}"
+                    )
+
+        # Process MoE layers
+        for layer_idx in range(
+            self.fd_config.model_config.start_layer_index,
+            self.fd_config.model_config.start_layer_index + self.fd_config.model_config.num_nextn_predict_layers,
+        ):
+            _add_layer_mappings(layer_idx)
+
+        self._complete_missing_mappings()
+
+        return self.infer_to_train_mapping
diff --git a/tests/ci_use/GLM-45-AIR/baseline.txt b/tests/ci_use/GLM-45-AIR/baseline.txt
index bddb29fdac..4ebb05f0ce 100644
--- a/tests/ci_use/GLM-45-AIR/baseline.txt
+++ b/tests/ci_use/GLM-45-AIR/baseline.txt
@@ -2,12 +2,26 @@ lm_head.linear.weight
 lm_head.linear.weight:lm_head.weight
 model.embed_tokens.embeddings.weight
 model.embed_tokens.embeddings.weight:model.embed_tokens.weight
+model.layers.0.eh_proj.linear.weight:model.layers.0.eh_proj.linear.weight
+model.layers.0.enorm.weight:model.layers.0.enorm.weight
+model.layers.0.hnorm.weight:model.layers.0.hnorm.weight
 model.layers.0.input_layernorm.weight
 model.layers.0.input_layernorm.weight:model.layers.0.input_layernorm.weight
 model.layers.0.mlp.down_proj.weight
 model.layers.0.mlp.down_proj.weight:model.layers.0.mlp.down_proj.weight
 model.layers.0.mlp.up_gate_proj.weight
 model.layers.0.mlp.up_gate_proj.weight:model.layers.0.mlp.up_gate_proj.weight
+model.layers.0.mtp_block.input_layernorm.weight:model.layers.0.mtp_block.input_layernorm.weight
+model.layers.0.mtp_block.mlp.experts.down_proj_weight:model.layers.0.mtp_block.mlp.experts.down_proj_weight
+model.layers.0.mtp_block.mlp.experts.up_gate_proj_weight:model.layers.0.mtp_block.mlp.experts.up_gate_proj_weight
+model.layers.0.mtp_block.mlp.gate.e_score_correction_bias:model.layers.0.mtp_block.mlp.gate.e_score_correction_bias
+model.layers.0.mtp_block.mlp.gate.weight:model.layers.0.mtp_block.mlp.gate.weight
+model.layers.0.mtp_block.mlp.shared_experts.down_proj.weight:model.layers.0.mtp_block.mlp.shared_experts.down_proj.weight
+model.layers.0.mtp_block.mlp.shared_experts.up_gate_proj.weight:model.layers.0.mtp_block.mlp.shared_experts.up_gate_proj.weight
+model.layers.0.mtp_block.post_attention_layernorm.weight:model.layers.0.mtp_block.post_attention_layernorm.weight
+model.layers.0.mtp_block.self_attn.o_proj.weight:model.layers.0.mtp_block.self_attn.o_proj.weight
+model.layers.0.mtp_block.self_attn.qkv_proj.bias:model.layers.0.mtp_block.self_attn.qkv_proj.bias
+model.layers.0.mtp_block.self_attn.qkv_proj.weight:model.layers.0.mtp_block.self_attn.qkv_proj.weight
 model.layers.0.post_attention_layernorm.weight
 model.layers.0.post_attention_layernorm.weight:model.layers.0.post_attention_layernorm.weight
 model.layers.0.self_attn.o_proj.weight
@@ -16,6 +30,7 @@ model.layers.0.self_attn.qkv_proj.bias
 model.layers.0.self_attn.qkv_proj.bias:model.layers.0.self_attn.qkv_proj.bias
 model.layers.0.self_attn.qkv_proj.weight
 model.layers.0.self_attn.qkv_proj.weight:model.layers.0.self_attn.qkv_proj.weight
+model.layers.0.shared_head.norm.weight:model.layers.0.shared_head.norm.weight
 model.layers.1.input_layernorm.weight
 model.layers.1.input_layernorm.weight:model.layers.1.input_layernorm.weight
 model.layers.1.mlp.experts.down_proj_weight
@@ -39,5 +54,45 @@ model.layers.1.self_attn.qkv_proj.bias
 model.layers.1.self_attn.qkv_proj.bias:model.layers.1.self_attn.qkv_proj.bias
 model.layers.1.self_attn.qkv_proj.weight
 model.layers.1.self_attn.qkv_proj.weight:model.layers.1.self_attn.qkv_proj.weight
+model.layers.2.eh_proj.weight:model.layers.2.eh_proj.weight
+model.layers.2.enorm.weight:model.layers.2.enorm.weight
+model.layers.2.hnorm.weight:model.layers.2.hnorm.weight
+model.layers.2.mlp.experts.down_proj_weight:['model.layers.2.mlp.experts.0.down_proj.weight', 'model.layers.2.mlp.experts.1.down_proj.weight', 'model.layers.2.mlp.experts.2.down_proj.weight', 'model.layers.2.mlp.experts.3.down_proj.weight', 'model.layers.2.mlp.experts.4.down_proj.weight', 'model.layers.2.mlp.experts.5.down_proj.weight', 'model.layers.2.mlp.experts.6.down_proj.weight', 'model.layers.2.mlp.experts.7.down_proj.weight', 'model.layers.2.mlp.experts.8.down_proj.weight', 'model.layers.2.mlp.experts.9.down_proj.weight', 'model.layers.2.mlp.experts.10.down_proj.weight', 'model.layers.2.mlp.experts.11.down_proj.weight', 'model.layers.2.mlp.experts.12.down_proj.weight', 'model.layers.2.mlp.experts.13.down_proj.weight', 'model.layers.2.mlp.experts.14.down_proj.weight', 'model.layers.2.mlp.experts.15.down_proj.weight', 'model.layers.2.mlp.experts.16.down_proj.weight', 'model.layers.2.mlp.experts.17.down_proj.weight', 'model.layers.2.mlp.experts.18.down_proj.weight', 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'model.layers.2.mlp.experts.126.up_gate_proj.weight', 'model.layers.2.mlp.experts.127.up_gate_proj.weight']
+model.layers.2.mlp.gate.e_score_correction_bias:model.layers.2.mlp.gate.e_score_correction_bias
+model.layers.2.mlp.gate.weight:model.layers.2.mlp.gate.weight
+model.layers.2.shared_head.head.weight:model.layers.2.shared_head.head.weight
+model.layers.2.shared_head.norm.weight:model.layers.2.shared_head.norm.weight
 model.norm.weight
 model.norm.weight:model.norm.weight
+mtp_layers.model.layers.0.eh_proj.linear.weight
+mtp_layers.model.layers.0.eh_proj.linear.weight:mtp_layers.model.layers.0.eh_proj.linear.weight
+mtp_layers.model.layers.0.enorm.weight
+mtp_layers.model.layers.0.enorm.weight:mtp_layers.model.layers.0.enorm.weight
+mtp_layers.model.layers.0.hnorm.weight
+mtp_layers.model.layers.0.hnorm.weight:mtp_layers.model.layers.0.hnorm.weight
+mtp_layers.model.layers.0.mtp_block.input_layernorm.weight
+mtp_layers.model.layers.0.mtp_block.input_layernorm.weight:mtp_layers.model.layers.0.mtp_block.input_layernorm.weight
+mtp_layers.model.layers.0.mtp_block.mlp.experts.down_proj_weight
+mtp_layers.model.layers.0.mtp_block.mlp.experts.down_proj_weight:mtp_layers.model.layers.0.mtp_block.mlp.experts.down_proj_weight
+mtp_layers.model.layers.0.mtp_block.mlp.experts.gate_correction_bias
+mtp_layers.model.layers.0.mtp_block.mlp.experts.up_gate_proj_weight
+mtp_layers.model.layers.0.mtp_block.mlp.experts.up_gate_proj_weight:mtp_layers.model.layers.0.mtp_block.mlp.experts.up_gate_proj_weight
+mtp_layers.model.layers.0.mtp_block.mlp.gate.e_score_correction_bias
+mtp_layers.model.layers.0.mtp_block.mlp.gate.e_score_correction_bias:mtp_layers.model.layers.0.mtp_block.mlp.gate.e_score_correction_bias
+mtp_layers.model.layers.0.mtp_block.mlp.gate.weight
+mtp_layers.model.layers.0.mtp_block.mlp.gate.weight:mtp_layers.model.layers.0.mtp_block.mlp.gate.weight
+mtp_layers.model.layers.0.mtp_block.mlp.shared_experts.down_proj.weight
+mtp_layers.model.layers.0.mtp_block.mlp.shared_experts.down_proj.weight:mtp_layers.model.layers.0.mtp_block.mlp.shared_experts.down_proj.weight
+mtp_layers.model.layers.0.mtp_block.mlp.shared_experts.up_gate_proj.weight
+mtp_layers.model.layers.0.mtp_block.mlp.shared_experts.up_gate_proj.weight:mtp_layers.model.layers.0.mtp_block.mlp.shared_experts.up_gate_proj.weight
+mtp_layers.model.layers.0.mtp_block.post_attention_layernorm.weight
+mtp_layers.model.layers.0.mtp_block.post_attention_layernorm.weight:mtp_layers.model.layers.0.mtp_block.post_attention_layernorm.weight
+mtp_layers.model.layers.0.mtp_block.self_attn.o_proj.weight
+mtp_layers.model.layers.0.mtp_block.self_attn.o_proj.weight:mtp_layers.model.layers.0.mtp_block.self_attn.o_proj.weight
+mtp_layers.model.layers.0.mtp_block.self_attn.qkv_proj.bias
+mtp_layers.model.layers.0.mtp_block.self_attn.qkv_proj.bias:mtp_layers.model.layers.0.mtp_block.self_attn.qkv_proj.bias
+mtp_layers.model.layers.0.mtp_block.self_attn.qkv_proj.weight
+mtp_layers.model.layers.0.mtp_block.self_attn.qkv_proj.weight:mtp_layers.model.layers.0.mtp_block.self_attn.qkv_proj.weight
+mtp_layers.model.layers.0.shared_head.norm.weight
+mtp_layers.model.layers.0.shared_head.norm.weight:mtp_layers.model.layers.0.shared_head.norm.weight
diff --git a/tests/rl/test_rollout_model.py b/tests/rl/test_rollout_model.py
index 4d720bcc2a..589362192b 100644
--- a/tests/rl/test_rollout_model.py
+++ b/tests/rl/test_rollout_model.py
@@ -205,6 +205,7 @@ def test_glm4moe_mapping_removes_gate_correction():
             "model.layers.0.mlp.experts.gate_correction_bias",
         ],
     )
+    dummy.num_nextn_predict_layers = 0
     mappings = dummy.get_name_mappings_to_training()
     # Cover gate/experts aggregation and dropping gate_correction_bias
     assert "model.layers.0.mlp.experts.up_gate_proj_weight" in mappings