diff --git a/bigframes/session/executor.py b/bigframes/session/executor.py
index 170f0ac086..a84861878a 100644
--- a/bigframes/session/executor.py
+++ b/bigframes/session/executor.py
@@ -379,11 +379,12 @@ def _run_execute_query(
             job_config.maximum_bytes_billed = (
                 bigframes.options.compute.maximum_bytes_billed
             )
-        # Note: add_labels is global scope which may have unexpected effects
-        bq_io.add_labels(job_config, api_name=api_name)
 
         if not self.strictly_ordered:
             job_config.labels["bigframes-mode"] = "unordered"
+
+        # Note: add_labels is global scope which may have unexpected effects
+        bq_io.add_labels(job_config, api_name=api_name)
         try:
             query_job = self.bqclient.query(sql, job_config=job_config)
             return (
diff --git a/tests/system/small/test_series.py b/tests/system/small/test_series.py
index b906f452b7..5bb20e2714 100644
--- a/tests/system/small/test_series.py
+++ b/tests/system/small/test_series.py
@@ -2768,20 +2768,25 @@ def test_series_case_when(scalars_dfs_maybe_ordered):
 
     # TODO(tswast): pandas case_when appears to assume True when a value is
     # null. I suspect this should be considered a bug in pandas.
-    bf_result = bf_series.case_when(
-        [
-            ((bf_series > 100).fillna(True), bf_series - 1),
-            ((bf_series > 0).fillna(True), pd.NA),
-            ((bf_series < -100).fillna(True), -1000),
-        ]
-    ).to_pandas()
-    pd_result = pd_series.case_when(
-        [
-            (pd_series > 100, pd_series - 1),
-            (pd_series > 0, pd.NA),
-            (pd_series < -100, -1000),
-        ]
+
+    # Generate 150 conditions to test case_when with a large number of conditions
+    bf_conditions = (
+        [((bf_series > 645).fillna(True), bf_series - 1)]
+        + [((bf_series > (-100 + i * 5)).fillna(True), i) for i in range(148, 0, -1)]
+        + [((bf_series <= -100).fillna(True), pd.NA)]
     )
+
+    pd_conditions = (
+        [((pd_series > 645), pd_series - 1)]
+        + [((pd_series > (-100 + i * 5)), i) for i in range(148, 0, -1)]
+        + [(pd_series <= -100, pd.NA)]
+    )
+
+    assert len(bf_conditions) == 150
+
+    bf_result = bf_series.case_when(bf_conditions).to_pandas()
+    pd_result = pd_series.case_when(pd_conditions)
+
     pd.testing.assert_series_equal(
         bf_result,
         pd_result.astype(pd.Int64Dtype()),