diff --git a/AI_Web_Scraper/model_downloader.py b/AI_Web_Scraper/model_downloader.py
index 96ded6c..9eddeba 100644
--- a/AI_Web_Scraper/model_downloader.py
+++ b/AI_Web_Scraper/model_downloader.py
@@ -1,6 +1,6 @@
 import os
 import json
-from transformers import AutoModelForCausalLM, AutoTokenizer
+from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
 from huggingface_hub import HfApi
 
 def download_model(config_path='./config.json'):
@@ -12,6 +12,8 @@ def download_model(config_path='./config.json'):
 
     model_name = config['model_name']
     local_path = config['model_local_path']
+    model_settings = config.get('model_settings', {})
+    use_quantization = model_settings.get('use_quantization', False)
 
     if not os.path.exists(local_path):
         os.makedirs(local_path)
@@ -19,10 +21,21 @@ def download_model(config_path='./config.json'):
     print(f"모델 {model_name}을 {local_path}에 다운로드 중...")
 
     try:
+        # 양자화 설정 적용
+        if use_quantization:
+            print("8bit 양자화 적용")
+            quantization_config = BitsAndBytesConfig(
+                load_in_8bit=True,
+                llm_int8_enable_fp32_cpu_offload=True
+            )
+        else:
+            quantization_config = None
+
         model = AutoModelForCausalLM.from_pretrained(
             model_name,
             cache_dir=local_path,
-            device_map="auto",  # GPU 자동 할당
+            quantization_config=quantization_config,
+            device_map="cpu",  # 다운로드 시 CPU에 로드하여 메모리 절약
             torch_dtype="auto"
         )
         tokenizer = AutoTokenizer.from_pretrained(