diff --git a/tests/distributed/test_pipeline_partition.py b/tests/distributed/test_pipeline_partition.py
index 3ed104820b4..18c5be29c5c 100644
--- a/tests/distributed/test_pipeline_partition.py
+++ b/tests/distributed/test_pipeline_partition.py
@@ -34,3 +34,27 @@ def test_custom_layer_partition():
     # Wrong number of layers
     with pytest.raises(ValueError):
         _verify("5,5,5,5", 21, 4, [(0, 5), (5, 10), (10, 15), (15, 20)])
+
+
+@pytest.mark.parametrize(
+    "num_hidden_layers,pp_size,pp_rank,indices",
+    [
+        # pp_size 2
+        (2, 2, 0, (0, 1)),
+        (2, 2, 1, (1, 2)),
+        (3, 2, 0, (0, 2)),
+        (3, 2, 1, (2, 3)),
+        # pp_size 3
+        (3, 3, 0, (0, 1)),
+        (3, 3, 1, (1, 2)),
+        (3, 3, 2, (2, 3)),
+        (4, 3, 0, (0, 1)),
+        (4, 3, 1, (1, 3)),
+        (4, 3, 2, (3, 4)),
+        (5, 3, 0, (0, 2)),
+        (5, 3, 1, (2, 4)),
+        (5, 3, 2, (4, 5)),
+    ])
+def test_uneven_auto_partition(num_hidden_layers: int, pp_size: int,
+                               pp_rank: int, indices: tuple[int, int]):
+    assert indices == get_pp_indices(num_hidden_layers, pp_rank, pp_size)
diff --git a/vllm/distributed/utils.py b/vllm/distributed/utils.py
index 79f9a84b476..d6fca4f0221 100644
--- a/vllm/distributed/utils.py
+++ b/vllm/distributed/utils.py
@@ -67,8 +67,17 @@ def split_tensor_along_last_dim(
 def get_pp_indices(num_hidden_layers: int, pp_rank: int,
                    pp_size: int) -> Tuple[int, int]:
     """Try to evenly distribute layers across partitions.
+
     If the number of layers is not divisible by the number of partitions,
-    the last partition will have the remaining layers.
+    the remaining layers are evenly distributed across all but the last
+    partition. The last partition is excluded because it often contains an
+    additional norm layer and we are attempting to balance compute.
+
+    If `pp_size > 2` and the number of remaining layers is
+    `0 < x <= pp_size - 2` then the remaining layers are evenly distributed
+    across the middle partitions. The first and last partitions are excluded
+    because they contain the input and output embeddings respectively and we
+    are attempting to reduce maximum memory consumption across partitions.
     """
     partition_list_str = envs.VLLM_PP_LAYER_PARTITION
     if partition_list_str is not None:
@@ -84,15 +93,20 @@ def get_pp_indices(num_hidden_layers: int, pp_rank: int,
         if sum(partitions) != num_hidden_layers:
             raise ValueError(
                 f"{sum(partitions)=} does not match {num_hidden_layers=}.")
-        start_layer = sum(partitions[:pp_rank])
-        end_layer = start_layer + partitions[pp_rank]
     else:
         layers_per_partition = num_hidden_layers // pp_size
-        start_layer = pp_rank * layers_per_partition
-        end_layer = start_layer + layers_per_partition
+        partitions = [layers_per_partition for _ in range(pp_size)]
 
-        if pp_rank == pp_size - 1:
-            end_layer = num_hidden_layers
+        if remaining_layers := num_hidden_layers % pp_size:
+            for i in range(2, remaining_layers + 2):
+                partitions[-i] += 1
+            logger.info("Hidden layers were unevenly partitioned: %s",
+                        ",".join(str(p) for p in partitions))
+            logger.info("This can be manually overridden using the "
+                        "VLLM_PP_LAYER_PARTITION environment variable")
+
+    start_layer = sum(partitions[:pp_rank])
+    end_layer = start_layer + partitions[pp_rank]
 
     return (start_layer, end_layer)