diff --git a/src/diffusers/models/modeling_utils.py b/src/diffusers/models/modeling_utils.py
index 5f011c46e43d..d927f2418f84 100644
--- a/src/diffusers/models/modeling_utils.py
+++ b/src/diffusers/models/modeling_utils.py
@@ -270,7 +270,7 @@ def save_pretrained(
         save_function: Optional[Callable] = None,
         safe_serialization: bool = True,
         variant: Optional[str] = None,
-        max_shard_size: Union[int, str] = "5GB",
+        max_shard_size: Union[int, str] = "10GB",
         push_to_hub: bool = False,
         **kwargs,
     ):
@@ -293,10 +293,13 @@ def save_pretrained(
                 Whether to save the model using `safetensors` or the traditional PyTorch way with `pickle`.
             variant (`str`, *optional*):
                 If specified, weights are saved in the format `pytorch_model.<variant>.bin`.
-            max_shard_size (`int` or `str`, defaults to `"5GB"`):
+            max_shard_size (`int` or `str`, defaults to `"10GB"`):
                 The maximum size for a checkpoint before being sharded. Checkpoints shard will then be each of size
                 lower than this size. If expressed as a string, needs to be digits followed by a unit (like `"5GB"`).
-                If expressed as an integer, the unit is bytes.
+                If expressed as an integer, the unit is bytes. Note that this limit will be decreased after a certain
+                period of time (starting from Oct 2024) to allow users to upgrade to the latest version of `diffusers`.
+                This is to establish a common default size for this argument across different libraries in the Hugging
+                Face ecosystem (`transformers`, and `accelerate`, for example).
             push_to_hub (`bool`, *optional*, defaults to `False`):
                 Whether or not to push your model to the Hugging Face Hub after saving it. You can specify the
                 repository you want to push to with `repo_id` (will default to the name of `save_directory` in your