diff --git a/modules/sdnq/loader.py b/modules/sdnq/loader.py
index 242f1e83b..e50a83977 100644
--- a/modules/sdnq/loader.py
+++ b/modules/sdnq/loader.py
@@ -18,22 +18,25 @@ def get_module_names(model: ModelMixin) -> list:
 def save_sdnq_model(model: ModelMixin, model_path: str, max_shard_size: str = "10GB", is_pipeline: bool = False, sdnq_config: SDNQConfig = None) -> None:
     model.save_pretrained(model_path, max_shard_size=max_shard_size) # actual save
 
+    quantization_config_path = os.path.join(model_path, "quantization_config.json")
     if sdnq_config is not None: # if provided, save global config
-        sdnq_config.to_json_file(os.path.join(model_path, "quantization_config.json"))
+        sdnq_config.to_json_file(quantization_config_path)
 
     if is_pipeline:
         for module_name in get_module_names(model): # save per-module config if available
             module = getattr(model, module_name, None)
-            if (module is not None) and hasattr(module, "quantization_config") and isinstance(module.quantization_config, SDNQConfig):
-                module.quantization_config.to_json_file(os.path.join(model_path, module_name, "quantization_config.json"))
+            if module is None:
+                continue
+            module_quantization_config_path = os.path.join(model_path, module_name, "quantization_config.json")
+            if hasattr(module, "quantization_config") and isinstance(module.quantization_config, SDNQConfig):
+                module.quantization_config.to_json_file(module_quantization_config_path)
+            elif hasattr(module, "config"), hasattr(module.config, "quantization_config") and isinstance(module.config.quantization_config, SDNQConfig):
+                module.config.quantization_config.to_json_file(module_quantization_config_path)
     elif sdnq_config is None:
-        quantization_config = None
-        if hasattr(model, "quantization_config"):
-            quantization_config = model.quantization_config
-        elif hasattr(model, "config") and hasattr(model.config, "quantization_config"):
-            quantization_config = model.config.quantization_config
-        if quantization_config is not None:
-            quantization_config.to_json_file(os.path.join(model_path, "quantization_config.json"))
+        if hasattr(model, "quantization_config") and isinstance(model.quantization_config, SDNQConfig):
+            model.quantization_config.to_json_file(quantization_config_path)
+        elif hasattr(model, "config") and hasattr(model.config, "quantization_config") and isinstance(model.config.quantization_config, SDNQConfig):
+            model.config.quantization_config.to_json_file(quantization_config_path)
 
 
 def load_sdnq_model(model_path: str, model_cls: ModelMixin = None, file_name: str = None, dtype: torch.dtype = None, device: torch.device = 'cpu', dequantize_fp32: bool = None, use_quantized_matmul: bool = None, model_config: dict = None, quantization_config: dict = None) -> ModelMixin: