diff --git a/vllm_ascend/quantization/quant_config.py b/vllm_ascend/quantization/quant_config.py
index e742852e91..fd53f88efc 100644
--- a/vllm_ascend/quantization/quant_config.py
+++ b/vllm_ascend/quantization/quant_config.py
@@ -157,6 +157,17 @@ def is_layer_skipped_ascend(
                         f"Detected some but not all shards of {prefix} "
                         "are quantized. All shards of fused layers "
                         "to have the same precision.")
+        elif "experts" in prefix:
+            # For the experts' prefix (e.g., "model.layers.3.mlp.experts")
+            # Assume all experts within the same MLP use the same quantization method
+            experts_quant_description = [
+                self.quant_description[layer]
+                for layer in self.quant_description if prefix in layer
+            ]
+            is_skipped = any(
+                quantization == "FLOAT"
+                for quantization in experts_quant_description
+            )
         else:
             is_skipped = self.quant_description[prefix + '.weight'] == "FLOAT"
 
diff --git a/vllm_ascend/quantization/utils.py b/vllm_ascend/quantization/utils.py
index 6d914c0dad..749f5b257d 100644
--- a/vllm_ascend/quantization/utils.py
+++ b/vllm_ascend/quantization/utils.py
@@ -52,6 +52,16 @@ def get_linear_quant_type(quant_description: Dict[str, Any], prefix: str,
                     f"Not all shards of {prefix} are quantized with same quant type."
                     f"Shard {proj_name} uses {shard_quant_type}, but another shard"
                     f"use {quant_type}. Please check quantization config.")
+    elif "experts" in prefix:
+        # For the experts' prefix (e.g., "model.layers.3.mlp.experts")
+        # Assume all experts within the same MLP use the same quantization method
+        experts_quant_description = set(
+            quant_description[layer]
+            for layer in quant_description if prefix in layer
+        )
+        if not len(experts_quant_description) == 1:
+            raise RuntimeError(f"{prefix} has different quantization type: {experts_quant_description}.")
+        quant_type = experts_quant_description.pop()
     else:
         quant_type = quant_description[prefix + '.weight']
     return quant_type