diff --git a/deploy/lite/readme.md b/deploy/lite/readme.md
index 219cc83fe4487400e886e47e46cb30275ba72c14..bb52a02ea497a0611ea8210b5d5b4a9f9d429828 100644
--- a/deploy/lite/readme.md
+++ b/deploy/lite/readme.md
@@ -15,10 +15,9 @@ Paddle Lite是飞桨轻量化推理引擎，为手机、IOT端提供高效推理
 交叉编译环境用于编译 Paddle Lite 和 PaddleOCR 的C++ demo。
 支持多种开发环境，不同开发环境的编译流程请参考对应文档。
 
-1. [Docker](https://paddle-lite.readthedocs.io/zh/latest/user_guides/source_compile.html#docker)
-2. [Linux](https://paddle-lite.readthedocs.io/zh/latest/user_guides/source_compile.html#android)
-3. [MAC OS](https://paddle-lite.readthedocs.io/zh/latest/user_guides/source_compile.html#id13)
-4. [Windows](https://paddle-lite.readthedocs.io/zh/latest/demo_guides/x86.html#id4)
+1. [Docker](https://paddle-lite.readthedocs.io/zh/latest/source_compile/compile_env.html#docker)
+2. [Linux](https://paddle-lite.readthedocs.io/zh/latest/source_compile/compile_env.html#linux)
+3. [MAC OS](https://paddle-lite.readthedocs.io/zh/latest/source_compile/compile_env.html#mac-os)
 
 ### 1.2 准备预测库
 
@@ -28,15 +27,15 @@ Paddle Lite是飞桨轻量化推理引擎，为手机、IOT端提供高效推理
       |-|-|
       |Android|[arm7](https://paddlelite-data.bj.bcebos.com/Release/2.6.1/Android/inference_lite_lib.android.armv7.gcc.c++_static.with_extra.CV_ON.tar.gz) / [arm8](https://paddlelite-data.bj.bcebos.com/Release/2.6.1/Android/inference_lite_lib.android.armv8.gcc.c++_static.with_extra.CV_ON.tar.gz)|
       |IOS|[arm7](https://paddlelite-data.bj.bcebos.com/Release/2.6.1/iOS/inference_lite_lib.ios.armv7.with_extra.CV_ON.tar.gz) / [arm8](https://paddlelite-data.bj.bcebos.com/Release/2.6.1/iOS/inference_lite_lib.ios64.armv8.with_extra.CV_ON.tar.gz)|
-      |x86(Linux)|[预测库](https://paddlelite-data.bj.bcebos.com/Release/2.6.1/X86/Linux/inference_lite_lib.x86.linux.tar.gz)|
 
-      注：如果是从下Paddle-Lite[官网文档](https://paddle-lite.readthedocs.io/zh/latest/user_guides/release_lib.html#android-toolchain-gcc)下载的预测库，
-      注意选择`with_extra=ON，with_cv=ON`的下载链接。
+      注：1. 如果是从下Paddle-Lite[官网文档](https://paddle-lite.readthedocs.io/zh/latest/user_guides/release_lib.html#android-toolchain-gcc)下载的预测库，
+      注意选择`with_extra=ON，with_cv=ON`的下载链接。2. 如果使用量化的模型部署在端侧，建议使用Paddle-Lite develop分支编译预测库。
 
-- 2. 编译Paddle-Lite得到预测库，Paddle-Lite的编译方式如下：
+- 2. [建议]编译Paddle-Lite得到预测库，Paddle-Lite的编译方式如下：
 ```
 git clone https://github.com/PaddlePaddle/Paddle-Lite.git
 cd Paddle-Lite
+# 务必使用develop分支编译预测库
 git checkout develop
 ./lite/tools/build_android.sh  --arch=armv8  --with_cv=ON --with_extra=ON
 ```
@@ -82,9 +81,12 @@ Paddle-Lite 提供了多种策略来自动优化原始的模型，其中包括
 
 下述表格中提供了优化好的超轻量中文模型：
 
-|模型简介|检测模型|识别模型|Paddle-Lite版本|
-|-|-|-|-|
-|超轻量级中文OCR opt优化模型|[下载地址](https://paddleocr.bj.bcebos.com/deploy/lite/ch_det_mv3_db_opt.nb)|[下载地址](https://paddleocr.bj.bcebos.com/deploy/lite/ch_rec_mv3_crnn_opt.nb)|develop|
+|模型版本|模型简介|模型大小|检测模型|文本方向分类模型|识别模型|Paddle-Lite版本|
+|-|-|-|-|-|-|-|
+|V1.1|超轻量中文OCR 移动端模型|3.0M|[下载地址](https://paddleocr.bj.bcebos.com/20-09-22/mobile-slim/det/ch_ppocr_mobile_v1.1_det_prune_opt.nb)|[下载地址](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_cls_quant_opt.nb)|[下载地址](https://paddleocr.bj.bcebos.com/20-09-22/mobile-slim/rec/ch_ppocr_mobile_v1.1_rec_quant_opt.nb)|develop|
+|V1.0|轻量级中文OCR 移动端模型|8.6M|[下载地址](https://paddleocr.bj.bcebos.com/deploy/lite/ch_det_mv3_db_opt.nb)|---|[下载地址](https://paddleocr.bj.bcebos.com/deploy/lite/ch_rec_mv3_crnn_opt.nb)|develop|
+
+注意：V1.1 3.0M 轻量模型是使用PaddleSlim优化后的，需要配合Paddle-Lite最新预测库使用。
 
 如果直接使用上述表格中的模型进行部署，可略过下述步骤，直接阅读 [2.2节](#2.2与手机联调)。
 
@@ -182,7 +184,7 @@ wget  https://paddleocr.bj.bcebos.com/ch_models/ch_rec_mv3_crnn_infer.tar && tar
  ```
 
  准备测试图像，以`PaddleOCR/doc/imgs/11.jpg`为例，将测试的图像复制到`demo/cxx/ocr/debug/`文件夹下。
- 准备lite opt工具优化后的模型文件，`ch_det_mv3_db_opt.nb，ch_rec_mv3_crnn_opt.nb`，放置在`demo/cxx/ocr/debug/`文件夹下。
+ 准备lite opt工具优化后的模型文件，比如使用`ch_det_mv3_db_opt.nb，ch_rec_mv3_crnn_opt.nb`，模型文件放置在`demo/cxx/ocr/debug/`文件夹下。
 
  执行完成后，ocr文件夹下将有如下文件格式：
 
diff --git a/deploy/lite/readme_en.md b/deploy/lite/readme_en.md
index bf2f4b2212bf4d362fe2127da66127ab05766668..ec7d1422eb82793c3e2958a9b22c5780fb936657 100644
--- a/deploy/lite/readme_en.md
+++ b/deploy/lite/readme_en.md
@@ -14,10 +14,9 @@ deployment solutions for end-side deployment issues.
 - Mobile phone (arm7 or arm8)
 
 ## 2. Build PaddleLite library
-[build for Docker](https://paddle-lite.readthedocs.io/zh/latest/user_guides/source_compile.html#docker)
-[build for Linux](https://paddle-lite.readthedocs.io/zh/latest/user_guides/source_compile.html#android)
-[build for MAC OS](https://paddle-lite.readthedocs.io/zh/latest/user_guides/source_compile.html#id13)
-[build for windows](https://paddle-lite.readthedocs.io/zh/latest/demo_guides/x86.html#id4)
+1. [Docker](https://paddle-lite.readthedocs.io/zh/latest/source_compile/compile_env.html#docker)
+2. [Linux](https://paddle-lite.readthedocs.io/zh/latest/source_compile/compile_env.html#linux)
+3. [MAC OS](https://paddle-lite.readthedocs.io/zh/latest/source_compile/compile_env.html#mac-os)
 
 ## 3. Download prebuild library for android and ios
 
@@ -25,7 +24,8 @@ deployment solutions for end-side deployment issues.
 |-|-|
 |Android|[arm7](https://paddlelite-data.bj.bcebos.com/Release/2.6.1/Android/inference_lite_lib.android.armv7.gcc.c++_static.with_extra.CV_ON.tar.gz) / [arm8](https://paddlelite-data.bj.bcebos.com/Release/2.6.1/Android/inference_lite_lib.android.armv8.gcc.c++_static.with_extra.CV_ON.tar.gz)|
 |IOS|[arm7](https://paddlelite-data.bj.bcebos.com/Release/2.6.1/iOS/inference_lite_lib.ios.armv7.with_extra.CV_ON.tar.gz) / [arm8](https://paddlelite-data.bj.bcebos.com/Release/2.6.1/iOS/inference_lite_lib.ios64.armv8.with_extra.CV_ON.tar.gz)|
-|x86(Linux)|[预测库](https://paddlelite-data.bj.bcebos.com/Release/2.6.1/X86/Linux/inference_lite_lib.x86.linux.tar.gz)|
+
+note: It is recommended to build prebuild library using [Paddle-Lite](https://github.com/PaddlePaddle/Paddle-Lite) develop branch if developer wants to deploy the [quantitative](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/deploy/slim/quantization/README_en.md) model to mobile phone.
 
 
 The structure of the prediction library is as follows:
@@ -64,9 +64,10 @@ Paddle Lite provides a variety of strategies to automatically optimize the origi
 If you use PaddleOCR 8.6M OCR model to deploy, you can directly download the optimized model.
 
 
-|Introduction|Detection model|Recognition model|Paddle Lite branch |
-|-|-|-|-|
-|lightweight Chinese OCR optimized model|[Download](https://paddleocr.bj.bcebos.com/deploy/lite/ch_det_mv3_db_opt.nb)|[Download](https://paddleocr.bj.bcebos.com/deploy/lite/ch_rec_mv3_crnn_opt.nb)|develop|
+|Version|Introduction|Model size|Detection model|Text Direction model|Recognition model|Paddle Lite branch |
+|-|-|-|-|-|-|
+|V1.1|extra-lightweight chinese OCR optimized model|3.0M|[Download](https://paddleocr.bj.bcebos.com/20-09-22/mobile-slim/det/ch_ppocr_mobile_v1.1_det_prune_opt.nb)|[Download](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_cls_quant_opt.nb)|[Download](https://paddleocr.bj.bcebos.com/20-09-22/mobile-slim/rec/ch_ppocr_mobile_v1.1_rec_quant_opt.nb)|develop|
+|V1.0|lightweight Chinese OCR optimized model|8.6M|[Download](https://paddleocr.bj.bcebos.com/deploy/lite/ch_det_mv3_db_opt.nb)|---|[Download](https://paddleocr.bj.bcebos.com/deploy/lite/ch_rec_mv3_crnn_opt.nb)|develop|
 
 If the model to be deployed is not in the above table, you need to follow the steps below to obtain the optimized model.