diff --git a/vllm/model_executor/model_loader/weight_utils.py b/vllm/model_executor/model_loader/weight_utils.py
index 8b2c5610f1f91..18f6f40b32f05 100644
--- a/vllm/model_executor/model_loader/weight_utils.py
+++ b/vllm/model_executor/model_loader/weight_utils.py
@@ -15,8 +15,7 @@
 import huggingface_hub.constants
 import numpy as np
 import torch
-from huggingface_hub import (HfFileSystem, hf_hub_download, scan_cache_dir,
-                             snapshot_download)
+from huggingface_hub import HfFileSystem, hf_hub_download, snapshot_download
 from safetensors.torch import load_file, safe_open, save_file
 from tqdm.auto import tqdm
 
@@ -239,7 +238,8 @@ def download_weights_from_hf(
     Returns:
         str: The path to the downloaded model weights.
     """
-    if not huggingface_hub.constants.HF_HUB_OFFLINE:
+    local_only = huggingface_hub.constants.HF_HUB_OFFLINE
+    if not local_only:
         # Before we download we look at that is available:
         fs = HfFileSystem()
         file_list = fs.ls(model_name_or_path, detail=False, revision=revision)
@@ -255,7 +255,6 @@ def download_weights_from_hf(
     # Use file lock to prevent multiple processes from
     # downloading the same model weights at the same time.
     with get_lock(model_name_or_path, cache_dir):
-        start_size = scan_cache_dir().size_on_disk
         start_time = time.perf_counter()
         hf_folder = snapshot_download(
             model_name_or_path,
@@ -264,13 +263,12 @@ def download_weights_from_hf(
             cache_dir=cache_dir,
             tqdm_class=DisabledTqdm,
             revision=revision,
-            local_files_only=huggingface_hub.constants.HF_HUB_OFFLINE,
+            local_files_only=local_only,
         )
-        end_time = time.perf_counter()
-        end_size = scan_cache_dir().size_on_disk
-        if end_size != start_size:
-            logger.info("Time took to download weights for %s: %.6f seconds",
-                        model_name_or_path, end_time - start_time)
+        time_taken = time.perf_counter() - start_time
+        if time_taken > 0.5:
+            logger.info("Time spent downloading weights for %s: %.6f seconds",
+                        model_name_or_path, time_taken)
     return hf_folder