diff --git a/test/assets/fakedata/draw_boxes_different_label_colors.png b/test/assets/fakedata/draw_boxes_different_label_colors.png
new file mode 100644
index 00000000000..72178930602
Binary files /dev/null and b/test/assets/fakedata/draw_boxes_different_label_colors.png differ
diff --git a/test/smoke_test.py b/test/smoke_test.py
index 3a44ae3efe9..647e2f45c8f 100644
--- a/test/smoke_test.py
+++ b/test/smoke_test.py
@@ -102,8 +102,9 @@ def main() -> None:
         smoke_test_torchvision_resnet50_classify("cuda")
 
         # TODO: remove once pytorch/pytorch#110436 is resolved
-        if sys.version_info < (3, 12, 0):
-            smoke_test_compile()
+        # Temporary Disabling compile test. Untill triton with Manylinux2014 is available
+        # if sys.version_info < (3, 12, 0):
+        #    smoke_test_compile()
 
     if torch.backends.mps.is_available():
         smoke_test_torchvision_resnet50_classify("mps")
diff --git a/test/test_utils.py b/test/test_utils.py
index e89bef4a6d9..8dfe3a1080f 100644
--- a/test/test_utils.py
+++ b/test/test_utils.py
@@ -116,6 +116,21 @@ def test_draw_boxes():
     assert_equal(img, img_cp)
 
 
+@pytest.mark.skipif(PILLOW_VERSION < (10, 1), reason="The reference image is only valid for PIL >= 10.1")
+def test_draw_boxes_with_coloured_labels():
+    img = torch.full((3, 100, 100), 255, dtype=torch.uint8)
+    labels = ["a", "b", "c", "d"]
+    colors = ["green", "#FF00FF", (0, 255, 0), "red"]
+    label_colors = ["green", "red", (0, 255, 0), "#FF00FF"]
+    result = utils.draw_bounding_boxes(img, boxes, labels=labels, colors=colors, fill=True, label_colors=label_colors)
+
+    path = os.path.join(
+        os.path.dirname(os.path.abspath(__file__)), "assets", "fakedata", "draw_boxes_different_label_colors.png"
+    )
+    expected = torch.as_tensor(np.array(Image.open(path))).permute(2, 0, 1)
+    assert_equal(result, expected)
+
+
 @pytest.mark.parametrize("fill", [True, False])
 def test_draw_boxes_dtypes(fill):
     img_uint8 = torch.full((3, 100, 100), 255, dtype=torch.uint8)
diff --git a/torchvision/utils.py b/torchvision/utils.py
index b69edcb572e..0c62db363f2 100644
--- a/torchvision/utils.py
+++ b/torchvision/utils.py
@@ -161,6 +161,7 @@ def draw_bounding_boxes(
     width: int = 1,
     font: Optional[str] = None,
     font_size: Optional[int] = None,
+    label_colors: Optional[Union[List[Union[str, Tuple[int, int, int]]], str, Tuple[int, int, int]]] = None,
 ) -> torch.Tensor:
 
     """
@@ -184,9 +185,12 @@ def draw_bounding_boxes(
             also search in other directories, such as the `fonts/` directory on Windows or `/Library/Fonts/`,
             `/System/Library/Fonts/` and `~/Library/Fonts/` on macOS.
         font_size (int): The requested font size in points.
+        label_colors (color or list of colors, optional): Colors for the label text.  See the description of the
+            `colors` argument for details.  Defaults to the same colors used for the boxes.
 
     Returns:
         img (Tensor[C, H, W]): Image Tensor of dtype uint8 with bounding boxes plotted.
+
     """
     import torchvision.transforms.v2.functional as F  # noqa
 
@@ -219,6 +223,10 @@ def draw_bounding_boxes(
         )
 
     colors = _parse_colors(colors, num_objects=num_boxes)
+    if label_colors:
+        label_colors = _parse_colors(label_colors, num_objects=num_boxes)
+    else:
+        label_colors = colors.copy()
 
     if font is None:
         if font_size is not None:
@@ -243,7 +251,7 @@ def draw_bounding_boxes(
     else:
         draw = ImageDraw.Draw(img_to_draw)
 
-    for bbox, color, label in zip(img_boxes, colors, labels):  # type: ignore[arg-type]
+    for bbox, color, label, label_color in zip(img_boxes, colors, labels, label_colors):  # type: ignore[arg-type]
         if fill:
             fill_color = color + (100,)
             draw.rectangle(bbox, width=width, outline=color, fill=fill_color)
@@ -252,7 +260,7 @@ def draw_bounding_boxes(
 
         if label is not None:
             margin = width + 1
-            draw.text((bbox[0] + margin, bbox[1] + margin), label, fill=color, font=txt_font)
+            draw.text((bbox[0] + margin, bbox[1] + margin), label, fill=label_color, font=txt_font)
 
     out = F.pil_to_tensor(img_to_draw)
     if original_dtype.is_floating_point: