diff --git a/apps/application/flow/step_node/reranker_node/impl/base_reranker_node.py b/apps/application/flow/step_node/reranker_node/impl/base_reranker_node.py
index 8b7fa053e..d1eef33d4 100644
--- a/apps/application/flow/step_node/reranker_node/impl/base_reranker_node.py
+++ b/apps/application/flow/step_node/reranker_node/impl/base_reranker_node.py
@@ -47,14 +47,15 @@ class BaseRerankerNode(IRerankerNode):
     def execute(self, question, reranker_setting, reranker_list, reranker_model_id,
                 **kwargs) -> NodeResult:
         documents = merge_reranker_list(reranker_list)
+        top_n = reranker_setting.get('top_n', 3)
         self.context['document_list'] = documents
         self.context['question'] = question
         reranker_model = get_model_instance_by_model_user_id(reranker_model_id,
-                                                             self.flow_params_serializer.data.get('user_id'))
+                                                             self.flow_params_serializer.data.get('user_id'),
+                                                             top_n=top_n)
         result = reranker_model.compress_documents(
             [Document(page_content=document) for document in documents if document is not None and len(document) > 0],
             question)
-        top_n = reranker_setting.get('top_n', 3)
         similarity = reranker_setting.get('similarity', 0.6)
         max_paragraph_char_number = reranker_setting.get('max_paragraph_char_number', 5000)
         r = filter_result(result, max_paragraph_char_number, top_n, similarity)
diff --git a/apps/setting/models_provider/impl/xinference_model_provider/model/reranker.py b/apps/setting/models_provider/impl/xinference_model_provider/model/reranker.py
index f32e1ee94..ed2db0f91 100644
--- a/apps/setting/models_provider/impl/xinference_model_provider/model/reranker.py
+++ b/apps/setting/models_provider/impl/xinference_model_provider/model/reranker.py
@@ -26,7 +26,7 @@ class XInferenceReranker(MaxKBBaseModel, BaseDocumentCompressor):
     @staticmethod
     def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
         return XInferenceReranker(server_url=model_credential.get('server_url'), model_uid=model_name,
-                                  api_key=model_credential.get('api_key'))
+                                  api_key=model_credential.get('api_key'), top_n=model_kwargs.get('top_n', 3))
 
     top_n: Optional[int] = 3