diff --git a/lmdeploy/cli/lite.py b/lmdeploy/cli/lite.py
index 499bace48..5ef989957 100644
--- a/lmdeploy/cli/lite.py
+++ b/lmdeploy/cli/lite.py
@@ -127,6 +127,8 @@ def add_parser_smooth_quant():
         ArgumentHelper.calib_search_scale(parser)
         ArgumentHelper.dtype(parser)
         ArgumentHelper.quant_dtype(parser)
+        ArgumentHelper.revision(parser)
+        ArgumentHelper.download_dir(parser)
 
     @staticmethod
     def auto_awq(args):
diff --git a/lmdeploy/lite/apis/smooth_quant.py b/lmdeploy/lite/apis/smooth_quant.py
index bfc19fd60..6114fdf89 100644
--- a/lmdeploy/lite/apis/smooth_quant.py
+++ b/lmdeploy/lite/apis/smooth_quant.py
@@ -1,5 +1,6 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 
+import os.path as osp
 from typing import Literal
 
 import fire
@@ -26,7 +27,9 @@ def smooth_quant(model: str,
                  dtype: Literal['float16', 'bfloat16', 'auto'] = 'auto',
                  device: str = 'cuda',
                  quant_dtype: Literal['int8', 'fp8', 'float8_e4m3fn',
-                                      'float8_e5m2'] = 'int8'):
+                                      'float8_e5m2'] = 'int8',
+                 revision: str = None,
+                 download_dir: str = None):
     if quant_dtype == 'fp8':
         quant_dtype = 'float8_e4m3fn'
 
@@ -37,6 +40,11 @@ def smooth_quant(model: str,
         q_dtype_info = torch.iinfo(quant_dtype)
 
     assert q_dtype_info.bits == w_bits
+    if not osp.exists(model):
+        print(f'can\'t find model from local_path {model}, '
+              'try to download from remote')
+        from lmdeploy.utils import get_model
+        model = get_model(model, revision=revision, download_dir=download_dir)
     model_path = model
     vl_model, model, tokenizer, work_dir = calibrate(model,
                                                      calib_dataset,