diff --git a/vllm/model_executor/layers/quantization/moe_wna16.py b/vllm/model_executor/layers/quantization/moe_wna16.py
index 0131a330f70d2..4bedb951a33f5 100644
--- a/vllm/model_executor/layers/quantization/moe_wna16.py
+++ b/vllm/model_executor/layers/quantization/moe_wna16.py
@@ -17,6 +17,9 @@ from vllm.model_executor.layers.fused_moe.layer import (
     FusedMoEMethodBase,
     FusedMoeWeightScaleSupported,
 )
+from vllm.model_executor.layers.fused_moe.unquantized_fused_moe_method import (
+    UnquantizedFusedMoEMethod,
+)
 from vllm.model_executor.layers.linear import LinearBase, UnquantizedLinearMethod
 from vllm.model_executor.layers.quantization import QuantizationMethods
 from vllm.model_executor.layers.quantization.base_config import (
@@ -162,6 +165,8 @@ class MoeWNA16Config(QuantizationConfig):
         self, layer: torch.nn.Module, prefix: str
     ) -> Optional["QuantizeMethodBase"]:
         if is_layer_skipped_quant(prefix, self.modules_to_not_convert):
+            if isinstance(layer, FusedMoE):
+                return UnquantizedFusedMoEMethod(layer.moe_config)
             return UnquantizedLinearMethod()
         elif isinstance(layer, LinearBase):
             # Avoid circular import