diff --git a/dask_sql/physical/utils/sort.py b/dask_sql/physical/utils/sort.py
index 5857a3321..2305ef1b6 100644
--- a/dask_sql/physical/utils/sort.py
+++ b/dask_sql/physical/utils/sort.py
@@ -19,30 +19,13 @@ def apply_sort(
     sort_null_first: List[bool],
 ) -> dd.DataFrame:
     # if we have a single partition, we can sometimes sort with map_partitions
-    if df.npartitions == 1:
-        if dask_cudf is not None and isinstance(df, dask_cudf.DataFrame):
-            # cudf only supports null positioning if `ascending` is a single boolean:
-            # https://github.com/rapidsai/cudf/issues/9400
-            if (all(sort_ascending) or not any(sort_ascending)) and not any(
-                sort_null_first[1:]
-            ):
-                return df.map_partitions(
-                    M.sort_values,
-                    by=sort_columns,
-                    ascending=all(sort_ascending),
-                    na_position="first" if sort_null_first[0] else "last",
-                )
-            if not any(sort_null_first):
-                return df.map_partitions(
-                    M.sort_values, by=sort_columns, ascending=sort_ascending
-                )
-        elif not any(sort_null_first[1:]):
-            return df.map_partitions(
-                M.sort_values,
-                by=sort_columns,
-                ascending=sort_ascending,
-                na_position="first" if sort_null_first[0] else "last",
-            )
+    if df.npartitions == 1 and (all(sort_null_first) or not any(sort_null_first)):
+        return df.map_partitions(
+            M.sort_values,
+            by=sort_columns,
+            ascending=sort_ascending,
+            na_position="first" if sort_null_first[0] else "last",
+        )
 
     # dask-cudf only supports ascending sort / nulls last:
     # https://github.com/rapidsai/cudf/pull/9250
diff --git a/tests/integration/test_sort.py b/tests/integration/test_sort.py
index 07cf33609..6d03220f6 100644
--- a/tests/integration/test_sort.py
+++ b/tests/integration/test_sort.py
@@ -216,23 +216,50 @@ def test_sort_with_nan_more_columns(gpu):
     )
     c.create_table("df", df)
 
-    df_result = (
-        c.sql(
-            "SELECT * FROM df ORDER BY a ASC NULLS FIRST, b DESC NULLS LAST, c ASC NULLS FIRST"
-        )
-        .c.compute()
-        .reset_index(drop=True)
+    df_result = c.sql(
+        "SELECT * FROM df ORDER BY a ASC NULLS FIRST, b DESC NULLS LAST, c ASC NULLS FIRST"
+    )
+    dd.assert_eq(
+        df_result,
+        xd.DataFrame(
+            {
+                "a": [float("nan"), float("nan"), 1, 1, 2, 2],
+                "b": [float("inf"), 5, 1, 1, 2, float("nan")],
+                "c": [5, 6, float("nan"), 1, 3, 4],
+            }
+        ),
+        check_index=False,
     )
-    dd.assert_eq(df_result, xd.Series([5, 6, float("nan"), 1, 3, 4]), check_names=False)
 
-    df_result = (
-        c.sql(
-            "SELECT * FROM df ORDER BY a ASC NULLS LAST, b DESC NULLS FIRST, c DESC NULLS LAST"
-        )
-        .c.compute()
-        .reset_index(drop=True)
+    df_result = c.sql(
+        "SELECT * FROM df ORDER BY a ASC NULLS LAST, b DESC NULLS FIRST, c DESC NULLS LAST"
+    )
+    dd.assert_eq(
+        df_result,
+        xd.DataFrame(
+            {
+                "a": [1, 1, 2, 2, float("nan"), float("nan")],
+                "b": [1, 1, float("nan"), 2, float("inf"), 5],
+                "c": [1, float("nan"), 4, 3, 5, 6],
+            }
+        ),
+        check_index=False,
+    )
+
+    df_result = c.sql(
+        "SELECT * FROM df ORDER BY a ASC NULLS FIRST, b DESC NULLS LAST, c DESC NULLS LAST"
+    )
+    dd.assert_eq(
+        df_result,
+        xd.DataFrame(
+            {
+                "a": [float("nan"), float("nan"), 1, 1, 2, 2],
+                "b": [float("inf"), 5, 1, 1, 2, float("nan")],
+                "c": [5, 6, 1, float("nan"), 3, 4],
+            }
+        ),
+        check_index=False,
     )
-    dd.assert_eq(df_result, xd.Series([1, float("nan"), 4, 3, 5, 6]), check_names=False)
 
 
 @pytest.mark.parametrize("gpu", [False, pytest.param(True, marks=pytest.mark.gpu)])