diff --git a/pandas/core/indexing.py b/pandas/core/indexing.py
index b74399ed86fbd..20dcc7c3dce5f 100644
--- a/pandas/core/indexing.py
+++ b/pandas/core/indexing.py
@@ -1557,7 +1557,16 @@ def _setitem_with_indexer(self, indexer, value):
             (blk,) = self.obj._mgr.blocks
             if 1 < blk.ndim:  # in case of dict, keys are indices
                 val = list(value.values()) if isinstance(value, dict) else value
-                take_split_path = not blk._can_hold_element(val)
+
+                # https://github.com/pandas-dev/pandas/issues/33198
+                if (
+                    isinstance(indexer, tuple)
+                    and com.is_null_slice(indexer[0])
+                    and self.ndim == len(indexer)
+                ):
+                    take_split_path = True
+                else:
+                    take_split_path = not blk._can_hold_element(val)
 
         # if we have any multi-indexes that have non-trivial slices
         # (not null slices) then we must take the split path, xref
diff --git a/pandas/tests/frame/indexing/test_iloc.py b/pandas/tests/frame/indexing/test_iloc.py
new file mode 100644
index 0000000000000..a29ab65554701
--- /dev/null
+++ b/pandas/tests/frame/indexing/test_iloc.py
@@ -0,0 +1,16 @@
+import numpy as np
+
+import pandas as pd
+import pandas._testing as tm
+
+
+def test_unsure_about_the_name_and_location():
+    # https://github.com/pandas-dev/pandas/issues/33198
+    arr = np.random.randn(10 ** 6).reshape(500, 2000).astype(np.float64)
+    df = pd.DataFrame(arr)
+    df.iloc[:, 1000:] = df.iloc[:, 1000:].astype(np.float32)
+    expected = pd.Series(
+        {np.dtype("float32"): 1000, np.dtype("float64"): 1000}, dtype="int64"
+    )
+    result = df.dtypes.value_counts()
+    tm.assert_series_equal(result, expected)