diff --git a/tests/python_client/bulk_insert/test_bulk_insert_perf.py b/tests/python_client/bulk_insert/test_bulk_insert_perf.py
index 4260ef5b8f..e952ce9646 100644
--- a/tests/python_client/bulk_insert/test_bulk_insert_perf.py
+++ b/tests/python_client/bulk_insert/test_bulk_insert_perf.py
@@ -113,9 +113,9 @@ class TestChaos(TestChaosBase):
         Path(data_dir).mkdir(parents=True, exist_ok=True)
         files = []
         if file_type == "json":
-            files = cf.gen_json_files_for_bulk_insert(data, schema, data_dir)
+            files = cf.gen_json_files_for_bulk_insert(data, schema, data_dir, nb=nb, dim=dim)
         if file_type == "npy":
-            files = cf.gen_npy_files_for_bulk_insert(data, schema, data_dir)
+            files = cf.gen_npy_files_for_bulk_insert(data, schema, data_dir, nb=nb, dim=dim)
         log.info("upload file to minio")
         client = Minio(minio_endpoint, access_key="minioadmin", secret_key="minioadmin", secure=False)
         for file_name in files:
diff --git a/tests/python_client/common/common_func.py b/tests/python_client/common/common_func.py
index 2f5e8fd0b5..bf491b265c 100644
--- a/tests/python_client/common/common_func.py
+++ b/tests/python_client/common/common_func.py
@@ -7,7 +7,7 @@ from functools import singledispatch
 import numpy as np
 import pandas as pd
 from sklearn import preprocessing
-
+from npy_append_array import NpyAppendArray
 from pymilvus import DataType
 from base.schema_wrapper import ApiCollectionSchemaWrapper, ApiFieldSchemaWrapper
 from common import common_type as ct
@@ -336,36 +336,56 @@ def gen_default_list_data_for_bulk_insert(nb=ct.default_nb, dim=ct.default_dim):
     int_values = [i for i in range(nb)]
     float_values = [np.float32(i) for i in range(nb)]
     string_values = [str(i) for i in range(nb)]
-    float_vec_values = gen_vectors(nb, dim)
+    float_vec_values = []  # placeholder for float_vec
     data = [int_values, float_values, string_values, float_vec_values]
     return data
 
 
-def gen_json_files_for_bulk_insert(data, schema, data_dir):
-    nb = len(data[0])
+def gen_json_files_for_bulk_insert(data, schema, data_dir, **kwargs):
+    nb = kwargs.get("nb", ct.default_nb)
+    dim = kwargs.get("dim", ct.default_dim)
     fields_name = [field.name for field in schema.fields]
-    entities = []
-    for i in range(nb):
-        entity_value = [field_values[i] for field_values in data]
-        entity = dict(zip(fields_name, entity_value))
-        entities.append(entity)
-    data_dict = {"rows": entities}
     file_name = "bulk_insert_data_source.json"
     files = ["bulk_insert_data_source.json"]
     data_source = os.path.join(data_dir, file_name)
     with open(data_source, "w") as f:
-        f.write(json.dumps(data_dict, indent=4, default=to_serializable))
+        f.write("{")
+        f.write("\n")
+        f.write('"rows":[')
+        f.write("\n")
+        for i in range(nb):
+            entity_value = [field_values[i] for field_values in data[:-1]]
+            vector = [random.random() for _ in range(dim)]
+            entity_value.append(vector)
+            entity = dict(zip(fields_name, entity_value))
+            f.write(json.dumps(entity, indent=4, default=to_serializable))
+            if i != nb - 1:
+                f.write(",")
+            f.write("\n")
+        f.write("]")
+        f.write("\n")
+        f.write("}")
     return files
 
 
-def gen_npy_files_for_bulk_insert(data, schema, data_dir):
+def gen_npy_files_for_bulk_insert(data, schema, data_dir, **kwargs):
+    nb = kwargs.get("nb", ct.default_nb)
+    dim = kwargs.get("dim", ct.default_dim)
     fields_name = [field.name for field in schema.fields]
     files = []
     for field in fields_name:
         files.append(f"{field}.npy")
     for i, file in enumerate(files):
         data_source = os.path.join(data_dir, file)
-        np.save(data_source, np.array(data[i]))
+        if "vector" in file:
+            log.info(f"generate {nb} vectors with dim {dim} for {data_source}")
+            with NpyAppendArray(data_source, "wb") as npaa:
+                for j in range(nb):
+                    vector = np.array([[random.random() for _ in range(dim)]])
+                    npaa.append(vector)
+
+        else:
+            np.save(data_source, np.array(data[i]))
     return files
 
 
diff --git a/tests/python_client/requirements.txt b/tests/python_client/requirements.txt
index 2e03b7419f..fdc5a2f276 100644
--- a/tests/python_client/requirements.txt
+++ b/tests/python_client/requirements.txt
@@ -33,6 +33,7 @@ timeout-decorator==0.5.0
 
 # for bulk insert test
 minio==7.1.5
+npy-append-array==0.9.15
 
 # for benchmark
 h5py==3.7.0