diff --git a/ppcls/modeling/architectures/distillation_models.py b/ppcls/modeling/architectures/distillation_models.py
new file mode 100644
index 0000000000000000000000000000000000000000..258627f8059eb9804f5b7cf15f6b44f621029b58
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+++ b/ppcls/modeling/architectures/distillation_models.py
@@ -0,0 +1,58 @@
+#copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
+#
+#Licensed under the Apache License, Version 2.0 (the "License");
+#you may not use this file except in compliance with the License.
+#You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+#Unless required by applicable law or agreed to in writing, software
+#distributed under the License is distributed on an "AS IS" BASIS,
+#WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#See the License for the specific language governing permissions and
+#limitations under the License.
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import math
+
+import paddle
+import paddle.fluid as fluid
+from paddle.fluid.param_attr import ParamAttr
+
+from .resnet_vd import ResNet50_vd
+from .mobilenet_v3 import MobileNetV3_large_x1_0
+from .resnext101_wsl import ResNeXt101_32x16d_wsl
+
+__all__ = [
+    'ResNet50_vd_distill_MobileNetV3_x1_0',
+    'ResNeXt101_32x16d_wsl_distill_ResNet50_vd'
+]
+
+
+class ResNet50_vd_distill_MobileNetV3_x1_0():
+    def net(self, input, class_dim=1000):
+        # student
+        student = MobileNetV3_large_x1_0()
+        out_student = student.net(input, class_dim=class_dim)
+        # teacher
+        teacher = ResNet50_vd()
+        out_teacher = teacher.net(input, class_dim=class_dim)
+        out_teacher.stop_gradient = True
+
+        return out_teacher, out_student
+
+
+class ResNeXt101_32x16d_wsl_distill_ResNet50_vd():
+    def net(self, input, class_dim=1000):
+        # student
+        student = ResNet50_vd()
+        out_student = student.net(input, class_dim=class_dim)
+        # teacher
+        teacher = ResNeXt101_32x16d_wsl()
+        out_teacher = teacher.net(input, class_dim=class_dim)
+        out_teacher.stop_gradient = True
+
+        return out_teacher, out_student