diff --git a/src/llmcompressor/modifiers/awq/base.py b/src/llmcompressor/modifiers/awq/base.py
index 6bc97b446..bc86ba25f 100644
--- a/src/llmcompressor/modifiers/awq/base.py
+++ b/src/llmcompressor/modifiers/awq/base.py
@@ -182,6 +182,8 @@ def validate_awq_after(model: "AWQModifier") -> "AWQModifier":
         ), "In AWQ, all config groups must use the same configuration for group_size"
 
         model._group_size = next(iter(group_size_set))
+        if model._group_size is None:
+            model._group_size = -1
 
         in_num_bits_set = set(
             group.input_activations.num_bits
@@ -460,14 +462,17 @@ def _apply_smoothing(self, model: Module) -> None:
                 weight = torch.cat([bl.weight for bl in balance_layers], dim=0)
                 org_shape = weight.shape
                 # The weights are reshaped to be organised by quantization group
-                weight = weight.view(-1, self._group_size)
+                if self._group_size > 0:
+                    weight = weight.view(-1, self._group_size)
                 # Calculates the relative magnitude of the weights within
                 # each of the quantization groups, and rescales each group
                 # individually so that each group has weights on a 0-1 scale.
                 weight.abs_()
                 weight.div_(weight.amax(dim=1, keepdim=True) + 1e-6)
-                # Resizes the rescaled weight matrix back up to its original dimensions
-                weight = weight.view(org_shape)
+                if self._group_size > 0:
+                    # Resizes the rescaled weight matrix back up to
+                    # its original dimensions
+                    weight = weight.view(org_shape)
                 # Gets the average rescaled magnitude for each output channel
                 w_mean = weight.mean(0)
                 del weight