diff --git a/core/general-server/op/general_response_op.cpp b/core/general-server/op/general_response_op.cpp
index 126accfd0a406f420f57eef4e04268e9081c744f..5667a174d9bb6e134e58de72524c60839dc82356 100644
--- a/core/general-server/op/general_response_op.cpp
+++ b/core/general-server/op/general_response_op.cpp
@@ -89,50 +89,41 @@ int GeneralResponseOp::inference() {
     output->set_engine_name(pre_name);
     FetchInst *fetch_inst = output->add_insts();
 
-    std::map<std::string, int> fetch_index_map;
-    for (int i = 0; i < in->size(); ++i) {
-      VLOG(2) << "index " << i << " var " << in->at(i).name;
-      fetch_index_map.insert(std::pair<std::string, int>(in->at(i).name, i));
-    }
-
     for (auto &idx : fetch_index) {
       Tensor *tensor = fetch_inst->add_tensor_array();
       tensor->set_elem_type(1);
-      int true_idx = fetch_index_map[model_config->_fetch_name[idx]];
       if (model_config->_is_lod_fetch[idx]) {
         VLOG(2) << "out[" << idx << "] " << model_config->_fetch_name[idx]
                 << " is lod_tensor";
-        for (int k = 0; k < in->at(true_idx).shape.size(); ++k) {
+        for (int k = 0; k < in->at(idx).shape.size(); ++k) {
           VLOG(2) << "shape[" << k << "]: " << in->at(idx).shape[k];
-          tensor->add_shape(in->at(true_idx).shape[k]);
+          tensor->add_shape(in->at(idx).shape[k]);
         }
       } else {
         VLOG(2) << "out[" << idx << "] " << model_config->_fetch_name[idx]
                 << " is tensor";
-        for (int k = 0; k < in->at(true_idx).shape.size(); ++k) {
-          VLOG(2) << "shape[" << k << "]: " << in->at(true_idx).shape[k];
-          tensor->add_shape(in->at(true_idx).shape[k]);
+        for (int k = 0; k < in->at(idx).shape.size(); ++k) {
+          VLOG(2) << "shape[" << k << "]: " << in->at(idx).shape[k];
+          tensor->add_shape(in->at(idx).shape[k]);
         }
       }
     }
 
     int var_idx = 0;
     for (auto &idx : fetch_index) {
-      int true_idx = fetch_index_map[model_config->_fetch_name[idx]];
       int cap = 1;
-      for (int j = 0; j < in->at(true_idx).shape.size(); ++j) {
-        cap *= in->at(true_idx).shape[j];
+      for (int j = 0; j < in->at(idx).shape.size(); ++j) {
+        cap *= in->at(idx).shape[j];
       }
-      if (in->at(true_idx).dtype == paddle::PaddleDType::INT64) {
+      if (in->at(idx).dtype == paddle::PaddleDType::INT64) {
         VLOG(2) << "Prepare float var [" << model_config->_fetch_name[idx]
                 << "].";
-        int64_t *data_ptr =
-            static_cast<int64_t *>(in->at(true_idx).data.data());
+        int64_t *data_ptr = static_cast<int64_t *>(in->at(idx).data.data());
         if (model_config->_is_lod_fetch[idx]) {
           FetchInst *fetch_p = output->mutable_insts(0);
-          for (int j = 0; j < in->at(true_idx).lod[0].size(); ++j) {
+          for (int j = 0; j < in->at(idx).lod[0].size(); ++j) {
             fetch_p->mutable_tensor_array(var_idx)->add_lod(
-                in->at(true_idx).lod[0][j]);
+                in->at(idx).lod[0][j]);
           }
           for (int j = 0; j < cap; ++j) {
             fetch_p->mutable_tensor_array(var_idx)->add_int64_data(data_ptr[j]);
@@ -145,15 +136,15 @@ int GeneralResponseOp::inference() {
         }
         VLOG(2) << "fetch var [" << model_config->_fetch_name[idx] << "] ready";
         var_idx++;
-      } else if (in->at(true_idx).dtype == paddle::PaddleDType::FLOAT32) {
+      } else if (in->at(idx).dtype == paddle::PaddleDType::FLOAT32) {
         VLOG(2) << "Prepare float var [" << model_config->_fetch_name[idx]
                 << "].";
-        float *data_ptr = static_cast<float *>(in->at(true_idx).data.data());
+        float *data_ptr = static_cast<float *>(in->at(idx).data.data());
         if (model_config->_is_lod_fetch[idx]) {
           FetchInst *fetch_p = output->mutable_insts(0);
-          for (int j = 0; j < in->at(true_idx).lod[0].size(); ++j) {
+          for (int j = 0; j < in->at(idx).lod[0].size(); ++j) {
             fetch_p->mutable_tensor_array(var_idx)->add_lod(
-                in->at(true_idx).lod[0][j]);
+                in->at(idx).lod[0][j]);
           }
           for (int j = 0; j < cap; ++j) {
             fetch_p->mutable_tensor_array(var_idx)->add_float_data(data_ptr[j]);
diff --git a/python/paddle_serving_client/io/__init__.py b/python/paddle_serving_client/io/__init__.py
index 93ae37056320c2c7d779c5bbfc4d004a1be4f639..034c85217cec70b73be499aaa342739ab5153c0a 100644
--- a/python/paddle_serving_client/io/__init__.py
+++ b/python/paddle_serving_client/io/__init__.py
@@ -33,7 +33,12 @@ def save_model(server_model_folder,
     executor = Executor(place=CPUPlace())
 
     feed_var_names = [feed_var_dict[x].name for x in feed_var_dict]
-    target_vars = list(fetch_var_dict.values())
+    #target_vars = list(fetch_var_dict.values())
+    target_vars = []
+    target_var_names = []
+    for key in sorted(fetch_var_dict.keys()):
+        target_vars.append(fetch_var_dict[key])
+        target_var_names.append(key)
 
     save_inference_model(
         server_model_folder,
@@ -64,7 +69,7 @@ def save_model(server_model_folder,
             feed_var.shape.extend(tmp_shape)
         config.feed_var.extend([feed_var])
 
-    for key in fetch_var_dict:
+    for key in target_var_names:
         fetch_var = model_conf.FetchVar()
         fetch_var.alias_name = key
         fetch_var.name = fetch_var_dict[key].name