diff --git a/src/zarr/core/buffer/cpu.py b/src/zarr/core/buffer/cpu.py
index 9da0059d0b..d1f3148da6 100644
--- a/src/zarr/core/buffer/cpu.py
+++ b/src/zarr/core/buffer/cpu.py
@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import numbers
 from typing import (
     TYPE_CHECKING,
     Any,
@@ -155,7 +156,10 @@ def create(
         fill_value: Any | None = None,
     ) -> Self:
         # np.zeros is much faster than np.full, and therefore using it when possible is better.
-        if fill_value is None or (isinstance(fill_value, int) and fill_value == 0):
+        # See https://numpy.org/doc/stable/reference/generated/numpy.isscalar.html#numpy-isscalar
+        # notes for why we use `numbers.Number`.
+        # Tehcnically `numbers.Number` need not support __eq__ hence the `ignore`.
+        if fill_value is None or (isinstance(fill_value, numbers.Number) and fill_value == 0):  # type: ignore[comparison-overlap]
             return cls(np.zeros(shape=tuple(shape), dtype=dtype, order=order))
         else:
             return cls(np.full(shape=tuple(shape), fill_value=fill_value, dtype=dtype, order=order))
diff --git a/tests/test_buffer.py b/tests/test_buffer.py
index b50e5abb67..d3fc8413b2 100644
--- a/tests/test_buffer.py
+++ b/tests/test_buffer.py
@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 from typing import TYPE_CHECKING, Literal
+from unittest import mock
 
 import numpy as np
 import pytest
@@ -243,3 +244,29 @@ def test_empty(
         assert result.flags.c_contiguous  # type: ignore[attr-defined]
     else:
         assert result.flags.f_contiguous  # type: ignore[attr-defined]
+
+
+@pytest.mark.parametrize("dtype", [np.int8, np.uint16, np.float32, int, float])
+@pytest.mark.parametrize("fill_value", [None, 0, 1])
+def test_no_full_with_zeros(
+    dtype: type[np.number[np.typing.NBitBase] | float],
+    fill_value: None | float,
+) -> None:
+    """Ensure that fill value of 0 (or None with a numeric dtype) does not trigger np.full, and instead triggers np.zeros"""
+    # full never called with fill 0
+    if fill_value == 0:
+        with mock.patch("numpy.full", side_effect=RuntimeError):
+            cpu.buffer_prototype.nd_buffer.create(
+                shape=(10,), dtype=dtype, fill_value=dtype(fill_value)
+            )
+    # full or zeros called appropriately based on fill value
+    with mock.patch(
+        "numpy.zeros" if fill_value == 0 or fill_value is None else "numpy.full",
+        side_effect=RuntimeError("called"),
+    ):
+        with pytest.raises(RuntimeError, match=r"called"):
+            cpu.buffer_prototype.nd_buffer.create(
+                shape=(10,),
+                dtype=dtype,
+                fill_value=dtype(fill_value) if fill_value is not None else fill_value,
+            )