diff --git a/tests/ut/ops/test_linear.py b/tests/ut/ops/test_linear.py
index 1153bfe..4634a69 100644
--- a/tests/ut/ops/test_linear.py
+++ b/tests/ut/ops/test_linear.py
@@ -4,6 +4,7 @@ from unittest import mock
 from unittest.mock import MagicMock, patch
 
 import torch
+from vllm import config
 
 from tests.ut.base import TestBase
 from vllm_ascend import ascend_config
@@ -106,6 +107,9 @@ class TestAscendRowParallelLinear(BaseLinearTest):
         linear(input_tensor)
 
     def test_oproj_tp(self):
+
+        config._current_vllm_config = MagicMock()
+
         ascend_config._ASCEND_CONFIG = MagicMock()
         ascend_config._ASCEND_CONFIG.oproj_tensor_parallel_size = 2
 
diff --git a/vllm_ascend/ops/linear.py b/vllm_ascend/ops/linear.py
index 81d7d9e..969cc97 100644
--- a/vllm_ascend/ops/linear.py
+++ b/vllm_ascend/ops/linear.py
@@ -26,6 +26,7 @@ import torch
 import torch.nn as nn
 import torch_npu
 from torch.nn.parameter import Parameter
+from vllm.config import get_current_vllm_config
 from vllm.distributed import divide
 from vllm.model_executor.layers.linear import (  # noqa
     WEIGHT_LOADER_V2_SUPPORTED, ColumnParallelLinear, LinearBase,
@@ -234,6 +235,13 @@ class AscendRowParallelLinear(RowParallelLinear):
         return_bias: bool = True,
         disable_tp: bool = False,
     ):
+        compilation_config = get_current_vllm_config().compilation_config
+        # TODO(shaopeng-666): Remove the visual check after the mm model reconstruction is complete.
+        if prefix in compilation_config.static_forward_context and \
+            "visual" not in prefix:
+            raise ValueError(f"Duplicate layer name: {prefix}")
+        compilation_config.static_forward_context[prefix] = self
+
         self.custom_op, self.tp_rank, self.tp_size = get_parallel_op(
             disable_tp, prefix, self, "row")
         # TODO(realliujiaxu): Replace the initialization code below with super().__init__ after linear of vllm supports custom comm group
diff --git a/vllm_ascend/ops/linear_op.py b/vllm_ascend/ops/linear_op.py
index 58a96fd..ff0462e 100644
--- a/vllm_ascend/ops/linear_op.py
+++ b/vllm_ascend/ops/linear_op.py
@@ -366,14 +366,23 @@ class SequenceRowParallelOp(CustomRowParallelOp):
                                              input_parallel,
                                              bias=bias_)
         else:
-            output_parallel = self.quant_method.apply(self.layer,
-                                                      input_parallel,
-                                                      bias=bias_)
-            output = torch.ops.vllm.maybe_pad_and_reduce(output_parallel)
+            output = torch.ops.vllm.matmul_and_reduce(input_parallel,
+                                                      self.prefix)
 
         output_bias = self.bias if self.skip_bias_add else None
         return output, output_bias
 
+    def matmul_and_reduce(self, input_parallel: torch.Tensor,
+                          bias_: Optional[Parameter]) -> torch.Tensor:
+        assert self.quant_method is not None
+        output_parallel = self.quant_method.apply(self.layer,
+                                                  input_parallel,
+                                                  bias=bias_)
+        from vllm_ascend.ops.register_custom_ops import \
+            _maybe_pad_and_reduce_impl
+        output = _maybe_pad_and_reduce_impl(output_parallel)
+        return output
+
     def update_attrs(self):
         super().update_attrs()
         self.input_is_parallel = self.layer.input_is_parallel
diff --git a/vllm_ascend/ops/register_custom_ops.py b/vllm_ascend/ops/register_custom_ops.py
index 5e2bbca..69e220e 100644
--- a/vllm_ascend/ops/register_custom_ops.py
+++ b/vllm_ascend/ops/register_custom_ops.py
@@ -235,6 +235,31 @@ def _maybe_all_reduce_tensor_model_parallel_impl(
         return tensor_model_parallel_all_reduce(final_hidden_states)
 
 
+def _matmul_and_reduce_impl(input_parallel: torch.Tensor,
+                            layer_name: str) -> torch.Tensor:
+    forward_context = get_forward_context()
+    self = forward_context.no_compile_layers[layer_name]
+    assert self.custom_op is not None
+    bias_ = None if (self.tp_rank > 0 or self.skip_bias_add) else self.bias
+    output = self.custom_op.matmul_and_reduce(input_parallel, bias_)
+
+    return output
+
+
+def _matmul_and_reduce_impl_fake(input_parallel: torch.Tensor,
+                                 layer_name: str) -> torch.Tensor:
+    forward_context = get_forward_context()
+    self = forward_context.no_compile_layers[layer_name]
+    num_tokens = input_parallel.size(0)
+    if forward_context.sp_enabled:
+        num_tokens = num_tokens // self.tp_size
+    output = torch.empty(size=(num_tokens, self.output_size_per_partition),
+                         device=input_parallel.device,
+                         dtype=input_parallel.dtype)
+
+    return output
+
+
 direct_register_custom_op(op_name="maybe_all_gather_and_maybe_unpad",
                           op_func=_maybe_all_gather_and_maybe_unpad_impl,
                           fake_impl=_maybe_all_gather_and_maybe_unpad_fake,
@@ -282,3 +307,9 @@ direct_register_custom_op(op_name="maybe_all_reduce_tensor_model_parallel",
                           fake_impl=lambda x: x,
                           mutates_args=[],
                           dispatch_key="PrivateUse1")
+
+direct_register_custom_op(op_name="matmul_and_reduce",
+                          op_func=_matmul_and_reduce_impl,
+                          fake_impl=_matmul_and_reduce_impl_fake,
+                          mutates_args=[],
+                          dispatch_key="PrivateUse1")