diff --git a/tools/aisbench.py b/tools/aisbench.py
index 9f37f126..2dc13b4d 100644
--- a/tools/aisbench.py
+++ b/tools/aisbench.py
@@ -28,7 +28,7 @@ import huggingface_hub
 import pandas as pd
 from modelscope import snapshot_download  # type: ignore
 
-BENCHMARK_HOME = os.getenv("BENCHMARK_HOME", os.path.abspath("."))
+BENCHMARK_HOME = os.getenv("BENCHMARK_HOME", os.path.abspath("./benchmark"))
 DATASET_CONF_DIR = os.path.join(BENCHMARK_HOME, "ais_bench", "benchmark",
                                 "configs", "datasets")
 REQUEST_CONF_DIR = os.path.join(BENCHMARK_HOME, "ais_bench", "benchmark",
@@ -74,9 +74,13 @@ class AisbenchRunner:
                  host_ip: str = "localhost",
                  verify=True):
         self.model = model
-        self.dataset_path = maybe_download_from_modelscope(
-            aisbench_config["dataset_path"], repo_type="dataset")
-        self.model_path = maybe_download_from_modelscope(model)
+        self.dataset_path = aisbench_config.get("dataset_path_local")
+        if not self.dataset_path:
+            self.dataset_path = maybe_download_from_modelscope(
+                aisbench_config["dataset_path"], repo_type="dataset")
+        self.model_path = aisbench_config.get("model_path")
+        if not self.model_path:
+            self.model_path = maybe_download_from_modelscope(model)
         assert self.dataset_path is not None and self.model_path is not None, \
             f"Failed to download dataset or model: dataset={self.dataset_path}, model={self.model_path}"
         self.port = port
diff --git a/tools/vllm_bench.py b/tools/vllm_bench.py
new file mode 100644
index 00000000..6cfcc2be
--- /dev/null
+++ b/tools/vllm_bench.py
@@ -0,0 +1,125 @@
+# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
+# Copyright 2023 The vLLM team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# This file is a part of the vllm-ascend project.
+#
+import json
+import logging
+import os
+import subprocess
+from datetime import datetime
+
+from .aisbench import maybe_download_from_modelscope
+
+
+class VllmbenchRunner:
+
+    def _run_vllm_bench_task(self):
+        vllm_bench_cmd = [
+            'vllm', 'bench', 'serve', '--backend', 'openai-chat',
+            '--trust-remote-code', '--served-model-name',
+            str(self.model_name), '--model', self.model_path, '--tokenizer',
+            self.model_path, '--metric-percentiles', '50,90,99', '--host',
+            self.host_ip, '--port',
+            str(self.port), '--save-result', '--result-filename',
+            self.result_filename, '--endpoint', '/v1/chat/completions',
+            '--ready-check-timeout-sec', '0'
+        ]
+        self._concat_config_args(vllm_bench_cmd)
+        print(f"running vllm_bench cmd: {' '.join(vllm_bench_cmd)}")
+        self.proc: subprocess.Popen = subprocess.Popen(vllm_bench_cmd,
+                                                       stdout=subprocess.PIPE,
+                                                       stderr=subprocess.PIPE,
+                                                       text=True)
+
+    def __init__(self,
+                 model_name: str,
+                 port: int,
+                 config: dict,
+                 model_path: str = "",
+                 host_ip: str = "localhost"):
+        self.model_name = model_name
+        self.model_path = model_path
+        if not self.model_path:
+            self.model_path = maybe_download_from_modelscope(model_name)
+        assert self.model_path is not None, \
+            f"Failed to download model: model={self.model_path}"
+        self.port = port
+        self.host_ip = host_ip
+        curr_time = datetime.now().strftime('%Y%m%d%H%M%S')
+        self.result_filename = f"result_vllm_bench_{curr_time}.json"
+        self.config = config
+
+        self._run_vllm_bench_task()
+        self._wait_for_task()
+        self._get_result()
+
+    def _concat_config_args(self, vllm_bench_cmd):
+        if "ignore_eos" in self.config:
+            if self.config["ignore_eos"]:
+                self.config["ignore_eos"] = ""
+            else:
+                self.config.pop("ignore_eos")
+        for key, value in self.config.items():
+            key = "--" + key.replace("_", "-")
+            vllm_bench_cmd += [key, str(value)]
+
+    def __enter__(self):
+        return self
+
+    def __exit__(self, exc_type, exc_value, traceback):
+        self.proc.terminate()
+        try:
+            self.proc.wait(8)
+        except subprocess.TimeoutExpired:
+            # force kill if needed
+            self.proc.kill()
+
+    def _wait_for_task(self):
+        result_msg = "========================="
+        while True:
+            line = self.proc.stdout.readline().strip()
+            if line:
+                print(line)
+            if result_msg in line:
+                return
+            if "ERROR" in line:
+                error_msg = f"Some errors happened to vllm_bench runtime, the first error is {line}"
+                raise RuntimeError(error_msg) from None
+
+    def _get_result(self):
+        result_file = os.path.join(os.getcwd(), self.result_filename)
+        print("Getting performance results from file: ", result_file)
+        with open(result_file, 'r', encoding='utf-8') as f:
+            self.result = json.load(f)
+
+
+def run_vllm_bench_case(model_name,
+                        port,
+                        config,
+                        model_path="",
+                        host_ip="localhost"):
+    try:
+        with VllmbenchRunner(model_name,
+                             port,
+                             config,
+                             model_path=model_path,
+                             host_ip=host_ip) as vllm_bench:
+            vllm_bench_result = vllm_bench.result
+    except Exception as e:
+        print(e)
+        error_msg = f"vllm_bench run failed, reason is {e}"
+        logging.error(error_msg)
+        assert False, f"vllm_bench run failed, reason is {e}"
+    return vllm_bench_result