diff --git a/flax/nnx/nn/linear.py b/flax/nnx/nn/linear.py
index f25433c96..67bf92855 100644
--- a/flax/nnx/nn/linear.py
+++ b/flax/nnx/nn/linear.py
@@ -251,6 +251,11 @@ def __call__(self, inputs: Array, out_sharding = None) -> Array:
 
     Args:
       inputs: The nd-array to be transformed.
+      out_sharding: Optional sharding specification (e.g.,
+        ``jax.sharding.PartitionSpec``) for the output array. When using JAX's
+        explicit sharding mode with a mesh context with ``AxisType.Explicit``.
+        If ``None`` (default), the compiler automatically determines output
+        sharding.
 
     Returns:
       The transformed input.
@@ -398,6 +403,11 @@ def __call__(self, inputs: Array, out_sharding = None) -> Array:
 
     Args:
       inputs: The nd-array to be transformed.
+      out_sharding: Optional sharding specification (e.g.,
+        ``jax.sharding.PartitionSpec``) for the output array. When using JAX's
+        explicit sharding mode with a mesh context with ``AxisType.Explicit``.
+        If ``None`` (default), the compiler automatically determines output
+        sharding.
 
     Returns:
       The transformed input.
@@ -532,6 +542,11 @@ def __call__(
         the rhs being the learnable kernel. Exactly one of ``einsum_str``
         in the constructor argument and call argument must be not None,
         while the other must be None.
+      out_sharding: Optional sharding specification (e.g.,
+        ``jax.sharding.PartitionSpec``) for the output array. When using JAX's
+        explicit sharding mode with a mesh context with ``AxisType.Explicit``.
+        If ``None`` (default), the compiler automatically determines output
+        sharding.
 
     Returns:
       The transformed input.