diff --git a/vllm/v1/core/kv_cache_utils.py b/vllm/v1/core/kv_cache_utils.py
index 2ed7ef7e0..3da3d7e7b 100644
--- a/vllm/v1/core/kv_cache_utils.py
+++ b/vllm/v1/core/kv_cache_utils.py
@@ -1040,12 +1040,14 @@ def _get_kv_cache_groups_uniform_page_size(
     min_num_layers = min([len(layers) for layers in same_type_layers.values()])
     group_size = min_num_layers
     max_num_layers = max([len(layers) for layers in same_type_layers.values()])
-    if max_num_layers < min_num_layers * 1.25:
-        # If the number of layers is not much larger than the minimum number of layers,
-        # use the maximum number of layers as the group size to avoid too many padding
-        # layers. A typical example is gpt-oss-20b + eagle, with 12 sw + 13 full. We
-        # pad it to (13 sw, 13 full) instead of (12 sw, 24 full). 1.25 is just a
-        # magic number to avoid too many padding layers.
+    if max_num_layers < min_num_layers * 1.5:
+        # If the number of layers is not much larger than the minimum number of
+        # layers, use the maximum number of layers as the group size to avoid
+        # too many padding layers. A typical example is gpt-oss-20b + eagle,
+        # with 12 sw + 13 full. We pad it to (13 sw, 13 full) instead of
+        # (12 sw, 24 full). 1.5 is a heuristic to avoid too many padding
+        # layers while accommodating speculative decoding drafters that add
+        # extra layers to one attention type.
         group_size = max_num_layers
     grouped_layers = []
     for layers in same_type_layers.values():