diff --git a/CHANGES.md b/CHANGES.md
index 4f9d67cc..e5afc31c 100644
--- a/CHANGES.md
+++ b/CHANGES.md
@@ -1,4 +1,8 @@
 
+# 6.2.8 (2023-12-11)
+
+* apply `discrete` colormap when the provided colormap does not have 256 values
+
 # 6.2.7 (2023-11-29)
 
 * Adjusting dataset latitude for WarpedVRT parameters calculation when EPSG:4326 dataset latitudes overflows EPSG:3857 min/max latitude (https://github.com/cogeotiff/rio-tiler/pull/660)
diff --git a/rio_tiler/colormap.py b/rio_tiler/colormap.py
index 437676d0..8c0fa7af 100644
--- a/rio_tiler/colormap.py
+++ b/rio_tiler/colormap.py
@@ -103,11 +103,11 @@ def apply_cmap(data: numpy.ndarray, colormap: ColorMapType) -> DataMaskType:
     if isinstance(colormap, Sequence):
         return apply_intervals_cmap(data, colormap)
 
-    # if colormap has more than 256 values OR its `max` key >= 256 we can't use
+    # if colormap has less or more than 256 values OR its `max` key >= 256 we can't use
     # rio_tiler.colormap.make_lut, because we don't want to create a `lookup table`
     # with more than 256 entries (256 x 4) array. In this case we use `apply_discrete_cmap`
     # which can work with arbitrary colormap dict.
-    if len(colormap) > 256 or max(colormap) >= 256 or min(colormap) < 0:
+    if len(colormap) != 256 or max(colormap) >= 256 or min(colormap) < 0:
         return apply_discrete_cmap(data, colormap)
 
     lookup_table = make_lut(colormap)
diff --git a/tests/test_cmap.py b/tests/test_cmap.py
index 56a2f322..f21ba33f 100644
--- a/tests/test_cmap.py
+++ b/tests/test_cmap.py
@@ -151,6 +151,9 @@ def test_apply_discrete_cmap():
     mask[2:5, 2:5] = 255
     mask[5:, 5:] = 255
     numpy.testing.assert_array_equal(m, mask)
+    dd, mm = colormap.apply_cmap(data, cm)
+    numpy.testing.assert_array_equal(dd, d)
+    numpy.testing.assert_array_equal(mm, m)
 
     data = data.astype("uint16")
     d, m = colormap.apply_discrete_cmap(data, cm)