diff --git a/vllm/model_executor/layers/mamba/mamba_mixer.py b/vllm/model_executor/layers/mamba/mamba_mixer.py
index 57e9772b0b600..b200d3ebf9c29 100644
--- a/vllm/model_executor/layers/mamba/mamba_mixer.py
+++ b/vllm/model_executor/layers/mamba/mamba_mixer.py
@@ -7,7 +7,7 @@
     get_tensor_model_parallel_rank, get_tensor_model_parallel_world_size)
 from vllm.model_executor.custom_op import CustomOp
 from vllm.model_executor.layers.layernorm import RMSNorm
-from vllm.model_executor.layers.linear import (ColumnParallelLinear,
+from vllm.model_executor.layers.linear import (ColumnParallelLinear, MergedColumnParallelLinear,
                                                RowParallelLinear)
 from vllm.model_executor.layers.mamba.ops.causal_conv1d import (
     causal_conv1d_fn, causal_conv1d_update)
@@ -58,8 +58,8 @@ def __init__(self,
         # doesn't allow to override it
         self.conv1d.weight.data = self.conv1d.weight.data.unsqueeze(1)
 
-        self.in_proj = ColumnParallelLinear(hidden_size,
-                                            intermediate_size * 2,
+        self.in_proj = MergedColumnParallelLinear(hidden_size,
+                                            [intermediate_size] * 2,
                                             bias=use_bias)
         # selective projection used to make dt, B and C input dependent
         self.x_proj = RowParallelLinear(