diff --git a/vllm_ascend/models/qwen3_moe.py b/vllm_ascend/models/qwen3_moe.py
index 29ab675525..fd5f2a5dc1 100644
--- a/vllm_ascend/models/qwen3_moe.py
+++ b/vllm_ascend/models/qwen3_moe.py
@@ -50,7 +50,9 @@
 from vllm_ascend.ops.fused_moe import AscendFusedMoE
 from vllm_ascend.ops.sequence_parallel import (MetadataForPadding,
                                                init_metadata_for_sp)
-
+from vllm_ascend.ops.layernorm import AddRMSNormW8A8Quant
+from vllm_ascend.quantization.w8a8 import AscendW8A8LinearMethod
+from vllm_ascend.quantization.quant_config import AscendQuantConfig
 
 class CustomSparseMoeBlock(Qwen3MoeSparseMoeBlock):
 
@@ -183,8 +185,18 @@ def __init__(
                                    hidden_act=config.hidden_act,
                                    quant_config=quant_config,
                                    prefix=f"{prefix}.mlp")
-        self.input_layernorm = RMSNorm(config.hidden_size,
-                                       eps=config.rms_norm_eps)
+
+        assert isinstance(quant_config, AscendQuantConfig), \
+            "Expected quant_config to be an instance of AscendQuantConfig"
+        if isinstance(self.self_attn.qkv_proj.quant_method.quant_method,
+                      AscendW8A8LinearMethod):
+            self.input_layernorm = AddRMSNormW8A8Quant(
+                config.hidden_size,
+                layer=self.self_attn.qkv_proj,
+                eps=config.rms_norm_eps)
+        else:
+            self.input_layernorm = RMSNorm(config.hidden_size,
+                                           eps=config.rms_norm_eps)
         self.post_attention_layernorm = RMSNorm(config.hidden_size,
                                                 eps=config.rms_norm_eps)