diff --git a/test/test_transforms_v2.py b/test/test_transforms_v2.py
index a9fd3bc5ec9..9f6817bb60d 100644
--- a/test/test_transforms_v2.py
+++ b/test/test_transforms_v2.py
@@ -4608,6 +4608,14 @@ def test_correctness_image(self, bits, fn):
 
         assert_equal(actual, expected)
 
+    @pytest.mark.parametrize("bits", [-1, 9, 2.1])
+    def test_error_functional(self, bits):
+        with pytest.raises(
+            TypeError,
+            match=re.escape(f"bits must be a positive integer in the range [0, 8], got {bits} instead."),
+        ):
+            F.posterize(make_image(dtype=torch.uint8), bits=bits)
+
 
 class TestSolarize:
     def _make_threshold(self, input, *, factor=0.5):
diff --git a/torchvision/transforms/v2/functional/_color.py b/torchvision/transforms/v2/functional/_color.py
index eb75f58cb7a..a3f187f84cf 100644
--- a/torchvision/transforms/v2/functional/_color.py
+++ b/torchvision/transforms/v2/functional/_color.py
@@ -460,6 +460,9 @@ def posterize(inpt: torch.Tensor, bits: int) -> torch.Tensor:
 @_register_kernel_internal(posterize, torch.Tensor)
 @_register_kernel_internal(posterize, tv_tensors.Image)
 def posterize_image(image: torch.Tensor, bits: int) -> torch.Tensor:
+    if not isinstance(bits, int) or not 0 <= bits <= 8:
+        raise TypeError(f"bits must be a positive integer in the range [0, 8], got {bits} instead.")
+
     if image.is_floating_point():
         levels = 1 << bits
         return image.mul(levels).floor_().clamp_(0, levels - 1).mul_(1.0 / levels)