diff --git a/tests/python_client/testcases/test_search.py b/tests/python_client/testcases/test_search.py
index 156051e612..103a8841b4 100644
--- a/tests/python_client/testcases/test_search.py
+++ b/tests/python_client/testcases/test_search.py
@@ -10131,8 +10131,8 @@ class TestSearchIterator(TestcaseBase):
 class TestSearchGroupBy(TestcaseBase):
     """ Test case of search group by """
 
-    @pytest.mark.tags(CaseLabel.L3)
-    @pytest.mark.parametrize("index_type, metric", zip(["FLAT", "IVF_FLAT", "HNSW"], ct.float_metrics))
+    @pytest.mark.tags(CaseLabel.L2)
+    @pytest.mark.parametrize("index_type, metric", zip(["DISKANN", "IVF_FLAT", "HNSW"], ct.float_metrics))
     @pytest.mark.parametrize("vector_data_type", ["FLOAT16_VECTOR", "FLOAT_VECTOR", "BFLOAT16_VECTOR"])
     def test_search_group_by_default(self, index_type, metric, vector_data_type):
         """
@@ -10147,9 +10147,8 @@ class TestSearchGroupBy(TestcaseBase):
         collection_w = self.init_collection_general(prefix, auto_id=True, insert_data=False, is_index=False,
                                                     vector_data_type=vector_data_type,
                                                     is_all_data_type=True, with_json=False)[0]
-        _index_params = {"index_type": index_type, "metric_type": metric, "params": {"M": 16, "efConstruction": 128}}
-        if index_type in ["IVF_FLAT", "FLAT"]:
-            _index_params = {"index_type": index_type, "metric_type": metric, "params": {"nlist": 128}}
+        _index_params = {"index_type": index_type, "metric_type": metric,
+                         "params": cf.get_index_params_params(index_type)}
         collection_w.create_index(ct.default_float_vec_field_name, index_params=_index_params)
         # insert with the same values for scalar fields
         for _ in range(50):
@@ -10160,7 +10159,7 @@ class TestSearchGroupBy(TestcaseBase):
         collection_w.create_index(ct.default_float_vec_field_name, index_params=_index_params)
         collection_w.load()
 
-        search_params = {"metric_type": metric, "params": {"ef": 128}}
+        search_params = {"params": cf.get_search_params_params(index_type)}
         nq = 2
         limit = 15
         search_vectors = cf.gen_vectors(nq, dim=ct.default_dim)
@@ -10206,9 +10205,11 @@ class TestSearchGroupBy(TestcaseBase):
                     top1_expr_pk = res_tmp[0][0].id
                     if top1_grpby_pk != top1_expr_pk:
                         dismatch += 1
-                        log.info(f"{grpby_field} on {metric} dismatch_item, top1_grpby_dis: {top1.distance}, top1_expr_dis: {res_tmp[0][0].distance}")
-                log.info(f"{grpby_field} on {metric}  top1_dismatch_num: {dismatch}, results_num: {results_num}, dismatch_rate: {dismatch / results_num}")
-                baseline = 1 if grpby_field == ct.default_bool_field_name else 0.2    # skip baseline check for boolean
+                        log.info(
+                            f"{grpby_field} on {metric} dismatch_item, top1_grpby_dis: {top1.distance}, top1_expr_dis: {res_tmp[0][0].distance}")
+                log.info(
+                    f"{grpby_field} on {metric}  top1_dismatch_num: {dismatch}, results_num: {results_num}, dismatch_rate: {dismatch / results_num}")
+                baseline = 1 if grpby_field == ct.default_bool_field_name else 0.4  # skip baseline check for boolean
                 assert dismatch / results_num <= baseline
                 # verify no dup values of the group_by_field in results
                 assert len(grpby_values) == len(set(grpby_values))