diff --git a/vllm_mindspore/model_executor/models/mf_models/deepseek_mtp.py b/vllm_mindspore/model_executor/models/mf_models/deepseek_mtp.py
index 3054d2ccfba2e12a2bee64fc3df8648580a54ed6..0a02ebf3c483cbbdfa98f17e6935573779885f92 100644
--- a/vllm_mindspore/model_executor/models/mf_models/deepseek_mtp.py
+++ b/vllm_mindspore/model_executor/models/mf_models/deepseek_mtp.py
@@ -108,7 +108,7 @@ class DeepseekV3MTPForCausalLM(MfModelBase):
 
 
     def load_weights(self, weights: Iterable[Tuple[str, Tensor]]) -> Set[str]:
-        weight_processor = DeepseekV3WeightProcessor(self.mf_config, self.network, False)
+        weight_processor = DeepseekV3WeightProcessor(self.mf_config, self.network, False, weights)
         weight_processor.load_safetensors_shard(self.mf_config.load_checkpoint, is_mtp_model=True)
         self.network.set_dynamic_inputs()
         dynamic_hidden_states = Tensor(shape=[None, None], dtype=self.mf_model_config.compute_dtype)
diff --git a/vllm_mindspore/model_executor/models/mf_models/deepseek_v3.py b/vllm_mindspore/model_executor/models/mf_models/deepseek_v3.py
index 3978ecb82c69d82ff452a2596cf45380cacad50c..5d74b0abf611d12eac08ae1e51fa05f51f4598c8 100644
--- a/vllm_mindspore/model_executor/models/mf_models/deepseek_v3.py
+++ b/vllm_mindspore/model_executor/models/mf_models/deepseek_v3.py
@@ -180,7 +180,7 @@ class DeepseekV3ForCausalLM(MfModelBase):
                 self.mf_config, model, self.network, infer_data, do_predict=True
             )
         else:
-            weight_processor = DeepseekV3WeightProcessor(self.mf_config, self.network, self.is_quant)
+            weight_processor = DeepseekV3WeightProcessor(self.mf_config, self.network, self.is_quant, weights)
             weight_processor.load_safetensors_shard(self.mf_config.load_checkpoint)
         return None
 
diff --git a/vllm_mindspore/model_executor/models/mf_models/deepseekv3_weight_processor.py b/vllm_mindspore/model_executor/models/mf_models/deepseekv3_weight_processor.py
index 4242ff3b6301571c8213753fd76502ce0f6b71e8..cd291aaa453337ff2e4929127a7030d099e78794 100644
--- a/vllm_mindspore/model_executor/models/mf_models/deepseekv3_weight_processor.py
+++ b/vllm_mindspore/model_executor/models/mf_models/deepseekv3_weight_processor.py
@@ -58,8 +58,8 @@ class DeepseekV3WeightProcessor(BaseWeightProcessor):
 
     """
 
-    def __init__(self, config, network, is_quant):
-        super().__init__(config, network, is_quant)
+    def __init__(self, config, network, is_quant, weights_iter):
+        super().__init__(config, network, is_quant, weights_iter)
         self.num_layers = self.config.model.model_config.num_layers
         self.expert_num = self.config.moe_config.expert_num
         self.moe_split_tp = self.moe_tp_size > 1
diff --git a/vllm_mindspore/model_executor/models/mf_models/qwen2.py b/vllm_mindspore/model_executor/models/mf_models/qwen2.py
index a24a0f1b98ed603b8f84f424a1b712c0a01f7a83..7ae515bfa8a409ada8d489b46bfb098550e1e103 100644
--- a/vllm_mindspore/model_executor/models/mf_models/qwen2.py
+++ b/vllm_mindspore/model_executor/models/mf_models/qwen2.py
@@ -75,7 +75,7 @@ class Qwen2ForCausalLM(MfModelBase):
         return network, network.lm_head
 
     def load_weights(self, weights: Iterable[Tuple[str, Tensor]]) -> Set[str]:
-        weight_processor = Qwen2WeightProcessor(self.mf_config, self.network, False)
+        weight_processor = Qwen2WeightProcessor(self.mf_config, self.network, False, weights)
         weight_processor.load_safetensors_shard(self.mf_config.load_checkpoint)
 
         return None
diff --git a/vllm_mindspore/model_executor/models/mf_models/qwen2_weight_processor.py b/vllm_mindspore/model_executor/models/mf_models/qwen2_weight_processor.py
index 07b55c6cc7d3f984f8998a837398716c8e0f5051..3887241b934704de7c1a4b79dc3a8731aecd9ed7 100644
--- a/vllm_mindspore/model_executor/models/mf_models/qwen2_weight_processor.py
+++ b/vllm_mindspore/model_executor/models/mf_models/qwen2_weight_processor.py
@@ -39,8 +39,8 @@ class Qwen2WeightProcessor(BaseWeightProcessor):
 
     """
 
-    def __init__(self, config, network, is_quant):
-        super().__init__(config, network, is_quant)
+    def __init__(self, config, network, is_quant, weights_iter):
+        super().__init__(config, network, is_quant, weights_iter)
 
     def infer_convert_outer_weight(self, src_hf_dir, hf_weight_map):
         """convert weight not in model"""
diff --git a/vllm_mindspore/model_executor/models/mf_models/weight_processor.py b/vllm_mindspore/model_executor/models/mf_models/weight_processor.py
index 85d3d170d6d74e7b1ce7cd8342297c60fead6a2d..aeeb452698c9365c15cc5d76a077835b4594c358 100644
--- a/vllm_mindspore/model_executor/models/mf_models/weight_processor.py
+++ b/vllm_mindspore/model_executor/models/mf_models/weight_processor.py
@@ -43,7 +43,7 @@ class BaseWeightProcessor:
 
     """
 
-    def __init__(self, config, network, is_quant):
+    def __init__(self, config, network, is_quant, weights_iter):
         self.config = config
         self.network = network
         self.is_quant = is_quant
@@ -71,6 +71,10 @@ class BaseWeightProcessor:
         self.parameter_dict = {}
         self.file_handles = {}
 
+        # Trigger the time initial of vllm native loading weights, make sure correct of Loading weights time costs.
+        for _, _ in weights_iter:
+            break
+
     def get_file_handles(self, filename):
         if filename not in self.file_handles:
             fp = safe_open(filename, framework="np")