diff --git a/vllm/model_executor/layers/quantization/compressed_tensors/schemes/compressed_tensors_w8a8_fp8.py b/vllm/model_executor/layers/quantization/compressed_tensors/schemes/compressed_tensors_w8a8_fp8.py
index 73cc8ce0d2a4b..1d4e4bd52adaa 100644
--- a/vllm/model_executor/layers/quantization/compressed_tensors/schemes/compressed_tensors_w8a8_fp8.py
+++ b/vllm/model_executor/layers/quantization/compressed_tensors/schemes/compressed_tensors_w8a8_fp8.py
@@ -41,10 +41,12 @@ def process_weights_after_loading(self, layer) -> None:
             )
 
             if current_platform.is_rocm():
+                input_scale = getattr(layer, 'input_scale', None)
+
                 weight, max_w_scale, input_scale = normalize_e4m3fn_to_e4m3fnuz(
                     weight=weight,
                     weight_scale=max_w_scale,
-                    input_scale=layer.input_scale)
+                    input_scale=input_scale)
                 if input_scale is not None:
                     layer.input_scale = Parameter(input_scale,
                                                   requires_grad=False)
@@ -57,11 +59,13 @@ def process_weights_after_loading(self, layer) -> None:
             weight = layer.weight
 
             if current_platform.is_rocm():
+                input_scale = getattr(layer, 'input_scale', None)
+
                 weight, weight_scale, input_scale = \
                     normalize_e4m3fn_to_e4m3fnuz(
                         weight=weight,
                         weight_scale=layer.weight_scale,
-                        input_scale=layer.input_scale)
+                        input_scale=input_scale)
                 if input_scale is not None:
                     layer.input_scale = Parameter(input_scale,
                                                   requires_grad=False)
@@ -76,7 +80,7 @@ def process_weights_after_loading(self, layer) -> None:
             raise ValueError(f"Unknown quantization strategy {self.strategy}")
 
         # INPUT SCALE
-        if self.is_static_input_scheme:
+        if self.is_static_input_scheme and hasattr(layer, 'input_scale'):
             layer.input_scale = Parameter(layer.input_scale.max(),
                                           requires_grad=False)
         else: