diff --git a/monai/networks/nets/diffusion_model_unet.py b/monai/networks/nets/diffusion_model_unet.py
index cb0c69d033..fe627c7e24 100644
--- a/monai/networks/nets/diffusion_model_unet.py
+++ b/monai/networks/nets/diffusion_model_unet.py
@@ -1529,9 +1529,9 @@ class DiffusionModelUNet(nn.Module):
         upcast_attention: if True, upcast attention operations to full precision.
         dropout_cattn: if different from zero, this will be the dropout value for the cross-attention layers.
         include_fc: whether to include the final linear layer. Default to True.
-        use_combined_linear: whether to use a single linear layer for qkv projection, default to True.
+        use_combined_linear: whether to use a single linear layer for qkv projection, default to False.
         use_flash_attention: if True, use Pytorch's inbuilt flash attention for a memory efficient attention mechanism
-            (see https://pytorch.org/docs/2.2/generated/torch.nn.functional.scaled_dot_product_attention.html).
+            (see https://pytorch.org/docs/2.2/generated/torch.nn.functional.scaled_dot_product_attention.html), default to False.
     """
 
     def __init__(