diff --git a/tests/python_client/testcases/test_collection.py b/tests/python_client/testcases/test_collection.py
index a90daff71747..1e2569e75f63 100644
--- a/tests/python_client/testcases/test_collection.py
+++ b/tests/python_client/testcases/test_collection.py
@@ -1060,7 +1060,7 @@ def test_collection_multi_sparse_vectors(self):
         # 2. create collection with multiple vectors
         c_name = cf.gen_unique_str(prefix)
         fields = [cf.gen_int64_field(is_primary=True), cf.gen_float_field(),
-                  cf.gen_float_vec_field(vector_data_type=ct.sparse_vector_data_type), cf.gen_float_vec_field(name="tmp", vector_data_type=sparse_vector_data_type)]
+                  cf.gen_float_vec_field(vector_data_type=ct.sparse_vector), cf.gen_float_vec_field(name="vec_sparse", vector_data_type=ct.sparse_vector)]
         schema = cf.gen_collection_schema(fields=fields)
         self.collection_wrap.init_collection(c_name, schema=schema,
                                              check_task=CheckTasks.check_collection_property,
diff --git a/tests/python_client/testcases/test_search.py b/tests/python_client/testcases/test_search.py
index 8b9627dc7e43..5243dfe12e76 100644
--- a/tests/python_client/testcases/test_search.py
+++ b/tests/python_client/testcases/test_search.py
@@ -12672,11 +12672,6 @@ def test_hybrid_search_sparse_normal(self):
             search_res = collection_w.search(vector, vector_name_list[i],
                                              default_search_params, default_limit,
                                              default_search_exp,
-                                             check_task=CheckTasks.check_search_results,
-                                             check_items={"nq": 1,
-                                                          "ids": insert_ids,
-                                                          # "limit": default_limit
-                                             }
                                              )[0]
             ids = search_res[0].ids
             for j in range(len(ids)):
@@ -12711,7 +12706,7 @@ def test_sparse_index_search(self, index):
         c_name = cf.gen_unique_str(prefix)
         schema = cf.gen_default_sparse_schema(auto_id=False)
         collection_w, _ = self.collection_wrap.init_collection(c_name, schema=schema)
-        data = cf.gen_default_list_sparse_data(nb=10000)
+        data = cf.gen_default_list_sparse_data(nb=4000)
         collection_w.insert(data)
         params = cf.get_index_params_params(index)
         index_params = {"index_type": index, "metric_type": "IP", "params": params}
@@ -12805,7 +12800,7 @@ def test_search_sparse_ratio(self, ratio, index):
         c_name = cf.gen_unique_str(prefix)
         schema = cf.gen_default_sparse_schema(auto_id=False)
         collection_w, _ = self.collection_wrap.init_collection(c_name, schema=schema)
-        data = cf.gen_default_list_sparse_data(nb=10000)
+        data = cf.gen_default_list_sparse_data(nb=4000)
         collection_w.insert(data)
         params = {"index_type": index, "metric_type": "IP", "params": {"drop_ratio_build": ratio}}
         collection_w.create_index(ct.default_sparse_vec_field_name, params, index_name=index)
@@ -12830,7 +12825,7 @@ def test_sparse_vector_search_output_field(self, index):
         c_name = cf.gen_unique_str(prefix)
         schema = cf.gen_default_sparse_schema()
         collection_w, _ = self.collection_wrap.init_collection(c_name, schema=schema)
-        data = cf.gen_default_list_sparse_data(nb=10000)
+        data = cf.gen_default_list_sparse_data(nb=4000)
         collection_w.insert(data)
         params = cf.get_index_params_params(index)
         index_params = {"index_type": index, "metric_type": "IP", "params": params}
@@ -12859,7 +12854,7 @@ def test_sparse_vector_search_iterator(self, index):
         c_name = cf.gen_unique_str(prefix)
         schema = cf.gen_default_sparse_schema()
         collection_w, _ = self.collection_wrap.init_collection(c_name, schema=schema)
-        data = cf.gen_default_list_sparse_data(nb=10000)
+        data = cf.gen_default_list_sparse_data(nb=4000)
         collection_w.insert(data)
         params = cf.get_index_params_params(index)
         index_params = {"index_type": index, "metric_type": "IP", "params": params}