diff --git a/README_cn.md b/README_cn.md
index c29a434b3dc231842104893ba80b3f1fb47b6107..db4dbdcc92171fe4209206b97547c375acef1830 100644
--- a/README_cn.md
+++ b/README_cn.md
@@ -86,6 +86,7 @@ PaddleDetection整理工业、农业、林业、交通、医疗、金融、能
   - 新增[少样本迁移学习](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/few-shot);
   - 新增[半监督检测模型](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/semi_det);
   - 新增[YOLOv8](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8);
+  - 更新[YOLOv6-v3.0](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6);
 - [🎗️产业特色模型|产业工具](#️产业特色模型产业工具-1)：
   - 发布**旋转框检测模型**[PP-YOLOE-R](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/rotate/ppyoloe_r)：Anchor-free旋转框检测SOTA模型，精度速度双高、云边一体，s/m/l/x四个模型适配不用算力硬件、部署友好，避免使用特殊算子，能够轻松使用TensorRT加速；
   - 发布**小目标检测模型**[PP-YOLOE-SOD](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/smalldet)：基于切图的端到端检测方案、基于原图的检测模型，精度达VisDrone开源最优；
@@ -116,7 +117,7 @@ PaddleDetection整理工业、农业、林业、交通、医疗、金融、能
 
   - **⚽️2022卡塔尔世界杯专题**
     - `文章传送门`：[世界杯决赛号角吹响！趁周末来搭一套足球3D+AI量化分析系统吧！](https://mp.weixin.qq.com/s/koJxjWDPBOlqgI-98UsfKQ)
-  
+
     <div align="center">
     <img src="https://user-images.githubusercontent.com/61035602/208036574-f151a7ff-a5f1-4495-9316-a47218a6576b.gif"  height = "250" caption='' />
     <p></p>
@@ -124,7 +125,7 @@ PaddleDetection整理工业、农业、林业、交通、医疗、金融、能
 
   - **🔍旋转框小目标检测专题**
     - `文章传送门`：[Yes, PP-YOLOE！80.73mAP、38.5mAP，旋转框、小目标检测能力双SOTA！](https://mp.weixin.qq.com/s/6ji89VKqoXDY6SSGkxS8NQ)
-  
+
     <div align="center">
     <img src="https://user-images.githubusercontent.com/61035602/208037368-5b9f01f7-afd9-46d8-bc80-271ccb5db7bb.png"  height = "220" caption='' />
     <p></p>
@@ -258,10 +259,10 @@ PaddleDetection整理工业、农业、林业、交通、医疗、金融、能
       <td>
         <ul>
           <li><a href="ppdet/modeling/losses/smooth_l1_loss.py">Smooth-L1</a></li>
-          <li><a href="ppdet/modeling/losses/detr_loss.py">Detr Loss</a></li> 
+          <li><a href="ppdet/modeling/losses/detr_loss.py">Detr Loss</a></li>
           <li><a href="ppdet/modeling/losses/fairmot_loss.py">Fairmot Loss</a></li>
           <li><a href="ppdet/modeling/losses/fcos_loss.py">Fcos Loss</a></li>
-          <li><a href="ppdet/modeling/losses/gfocal_loss.py">GFocal Loss</a></li> 
+          <li><a href="ppdet/modeling/losses/gfocal_loss.py">GFocal Loss</a></li>
           <li><a href="ppdet/modeling/losses/jde_loss.py">JDE Loss</a></li>
           <li><a href="ppdet/modeling/losses/keypoint_loss.py">KeyPoint Loss</a></li>
           <li><a href="ppdet/modeling/losses/solov2_loss.py">SoloV2 Loss</a></li>
@@ -293,7 +294,7 @@ PaddleDetection整理工业、农业、林业、交通、医疗、金融、能
             </ul>
           <li><b>Common</b></li>
         <ul>
-        <ul> 
+        <ul>
             <li><a href="ppdet/modeling/backbones/resnet.py#L41">Sync-BN</a></li>
             <li><a href="configs/gn/README.md">Group Norm</a></li>
             <li><a href="configs/dcn/README.md">DCNv2</a></li>
@@ -350,13 +351,14 @@ PaddleDetection整理工业、农业、林业、交通、医疗、金融、能
             <li><a href="configs/cascade_rcnn/README.md">Cascade-RCNN</a></li>
             <li><a href="configs/rcnn_enhance">PSS-Det</a></li>
             <li><a href="configs/retinanet/README.md">RetinaNet</a></li>
-            <li><a href="https://github.com/PaddlePaddle/PaddleYOLO">YOLOv3</a></li>  
-            <li><a href="https://github.com/PaddlePaddle/PaddleYOLO">YOLOv5</a></li>
-            <li><a href="https://github.com/PaddlePaddle/PaddleYOLO">YOLOX</a></li>  
-            <li><a href="https://github.com/PaddlePaddle/PaddleYOLO">YOLOv6</a></li>  
-            <li><a href="https://github.com/PaddlePaddle/PaddleYOLO">YOLOv7</a></li>
-            <li><a href="https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8">YOLOv8</a></li> 
-            <li><a href="https://github.com/PaddlePaddle/PaddleYOLO">RTMDet</a></li> 
+            <li><a href="configs/yolov3/README.md">YOLOv3</a></li>  
+            <li><a href="configs/yolof/README.md">YOLOF</a></li>  
+            <li><a href="configs/yolox/README.md">YOLOX</a></li>  
+            <li><a href="https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov5">YOLOv5</a></li>
+            <li><a href="https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov6">YOLOv6</a></li>  
+            <li><a href="https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov7">YOLOv7</a></li>
+            <li><a href="https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov8">YOLOv8</a></li>
+            <li><a href="https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/rtmdet">RTMDet</a></li>
             <li><a href="configs/ppyolo/README_cn.md">PP-YOLO</a></li>
             <li><a href="configs/ppyolo#pp-yolo-tiny">PP-YOLO-Tiny</a></li>
             <li><a href="configs/picodet">PP-PicoDet</a></li>
@@ -368,6 +370,7 @@ PaddleDetection整理工业、农业、林业、交通、医疗、金融、能
             <li><a href="configs/ssd/README.md">SSD</a></li>
             <li><a href="configs/centernet">CenterNet</a></li>
             <li><a href="configs/fcos">FCOS</a></li>  
+            <li><a href="configs/rotate/fcosr">FCOSR</a></li>  
             <li><a href="configs/ttfnet">TTFNet</a></li>
             <li><a href="configs/tood">TOOD</a></li>
             <li><a href="configs/gfl">GFL</a></li>
@@ -468,7 +471,7 @@ PaddleDetection整理工业、农业、林业、交通、医疗、金融、能
 - Cascade-Faster-RCNN为Cascade-Faster-RCNN-ResNet50vd-DCN，PaddleDetection将其优化到COCO数据mAP为47.8%时推理速度为20FPS
 - PP-YOLOE是对PP-YOLO v2模型的进一步优化，L版本在COCO数据集mAP为51.6%，Tesla V100预测速度78.1FPS
 - PP-YOLOE+是对PPOLOE模型的进一步优化，L版本在COCO数据集mAP为53.3%，Tesla V100预测速度78.1FPS
-- YOLOX和YOLOv5均为基于PaddleDetection复现算法，YOLOv5代码在PaddleYOLO中，参照PaddleYOLO_MODEL
+- YOLOX和YOLOv5均为基于PaddleDetection复现算法，YOLOv5代码在[PaddleYOLO](https://github.com/PaddlePaddle/PaddleYOLO)中，参照[PaddleYOLO_MODEL](docs/feature_models/PaddleYOLO_MODEL.md)
 - 图中模型均可在[📱模型库](#模型库)中获取
 </details>
 
@@ -805,4 +808,7 @@ PP-Vehicle囊括四大交通场景核心功能：车牌识别、属性识别、
 @misc{ppdet2019,
 title={PaddleDetection, Object detection and instance segmentation toolkit based on PaddlePaddle.},
 author={PaddlePaddle Authors},
-howpublished = {\url{https://github.com/PaddlePaddle/PaddleDetection}},
\ No newline at end of file
+howpublished = {\url{https://github.com/PaddlePaddle/PaddleDetection}},
+year={2019}
+}
+```
diff --git a/README_en.md b/README_en.md
index 25d8a474512d46e7d07f2892f2a5f178770ce88b..26454eb5feb0eb48ac64dd7eea4f4f67e9aea400 100644
--- a/README_en.md
+++ b/README_en.md
@@ -47,7 +47,7 @@
 
   - 💡 Cutting-edge algorithms：
 
-    - Release [PaddleYOLO](https://github.com/PaddlePaddle/PaddleYOLO) which overs classic and latest models of [YOLO family](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/docs/MODEL_ZOO_en.md): YOLOv3, PP-YOLOE (a real-time high-precision object detection model developed by Baidu PaddlePaddle), and cutting-edge detection algorithms such as YOLOv4, YOLOv5, YOLOX, YOLOv6, and YOLOv7
+    - Release [PaddleYOLO](https://github.com/PaddlePaddle/PaddleYOLO) which overs classic and latest models of [YOLO family](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/docs/MODEL_ZOO_en.md): YOLOv3, PP-YOLOE (a real-time high-precision object detection model developed by Baidu PaddlePaddle), and cutting-edge detection algorithms such as YOLOv4, YOLOv5, YOLOX, YOLOv6, YOLOv7 and YOLOv8
     - Newly add high precision detection model based on [ViT](configs/vitdet) backbone network, with a 55.7% mAP accuracy on COCO dataset; newly add multi-object tracking model [OC-SORT](configs/mot/ocsort); newly add [ConvNeXt](configs/convnext) backbone network.
 
   - 📋 Industrial applications: Newly add [Smart Fitness](https://aistudio.baidu.com/aistudio/projectdetail/4385813), [Fighting recognition](https://aistudio.baidu.com/aistudio/projectdetail/4086987?channelType=0&channel=0),[ and Visitor Analysis](https://aistudio.baidu.com/aistudio/projectdetail/4230123?channelType=0&channel=0).
@@ -118,14 +118,21 @@
             <li>PSS-Det</li>
             <li>RetinaNet</li>
             <li>YOLOv3</li>  
-            <li>PP-YOLOv1/v2</li>
+            <li>YOLOF</li>  
+            <li>YOLOX</li>  
+            <li>YOLOv5</li>  
+            <li>YOLOv6</li>  
+            <li>YOLOv7</li>  
+            <li>YOLOv8</li>  
+            <li>RTMDet</li>  
+            <li>PP-YOLO</li>
             <li>PP-YOLO-Tiny</li>
+            <li>PP-PicoDet</li>
+            <li>PP-YOLOv2</li>
             <li>PP-YOLOE</li>
             <li>PP-YOLOE+</li>
-            <li>PP-YOLOE-R</li>
             <li>PP-YOLOE-SOD</li>
-            <li>YOLOX</li>
-            <li>YOLOF</li>
+            <li>PP-YOLOE-R</li>
             <li>SSD</li>
             <li>CenterNet</li>
             <li>FCOS</li>  
@@ -133,7 +140,7 @@
             <li>TTFNet</li>
             <li>TOOD</li>
             <li>GFL</li>
-            <li>PP-PicoDet</li>
+            <li>GFLv2</li>
             <li>DETR</li>
             <li>Deformable DETR</li>
             <li>Swin Transformer</li>
diff --git a/docs/MODEL_ZOO_cn.md b/docs/MODEL_ZOO_cn.md
index 2eb099eec8831e45bf34fa8d1ff6883b2751bbb0..44bd25bceabaedad5c27b713ca1f9829250b21d5 100644
--- a/docs/MODEL_ZOO_cn.md
+++ b/docs/MODEL_ZOO_cn.md
@@ -28,7 +28,7 @@
 ## 通用设置
 
 - 所有模型均在COCO17数据集中训练和测试。
-- [YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov5)、[YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov6)和[YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov7)这3类模型的代码在[PaddleYOLO](https://github.com/PaddlePaddle/PaddleYOLO)中，**PaddleYOLO库开源协议为GPL 3.0**。
+- [YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov5)、[YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov6)、[YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov7)和[YOLOv8](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov8)这几类模型的代码在[PaddleYOLO](https://github.com/PaddlePaddle/PaddleYOLO)中，**PaddleYOLO库开源协议为GPL 3.0**。
 - 除非特殊说明，所有ResNet骨干网络采用[ResNet-B](https://arxiv.org/pdf/1812.01187)结构。
 - **推理时间(fps)**: 推理时间是在一张Tesla V100的GPU上通过'tools/eval.py'测试所有验证集得到，单位是fps(图片数/秒), cuDNN版本是7.5，包括数据加载、网络前向执行和后处理, batch size是1。
 
@@ -171,7 +171,7 @@ Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型
 
 请参考[YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov5)
 
-### YOLOv6
+### YOLOv6(v3.0)
 
 请参考[YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov6)
 
@@ -179,6 +179,10 @@ Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型
 
 请参考[YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov7)
 
+### YOLOv8
+
+请参考[YOLOv8](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov8)
+
 ### RTMDet
 
 请参考[RTMDet](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/rtmdet)
diff --git a/docs/MODEL_ZOO_en.md b/docs/MODEL_ZOO_en.md
index ac725bcf9a04831e72ffd3afcc4d66a954323950..057558f57e25a1e267c9a024c34f9f3f4d27bc1d 100644
--- a/docs/MODEL_ZOO_en.md
+++ b/docs/MODEL_ZOO_en.md
@@ -28,7 +28,7 @@
 ## General Settings
 
 - All models were trained and tested in the COCO17 dataset.
-- The codes of [YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov5),[YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov6) and [YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov7) can be found in [PaddleYOLO](https://github.com/PaddlePaddle/PaddleYOLO). Note that **the LICENSE of PaddleYOLO is GPL 3.0**.
+- The codes of [YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov5),[YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov6),[YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov7) and [YOLOv8](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov8) can be found in [PaddleYOLO](https://github.com/PaddlePaddle/PaddleYOLO). Note that **the LICENSE of PaddleYOLO is GPL 3.0**.
 - Unless special instructions, all the ResNet backbone network using [ResNet-B](https://arxiv.org/pdf/1812.01187) structure.
 - **Inference time (FPS)**: The reasoning time was calculated on a Tesla V100 GPU by `tools/eval.py` testing all validation sets in FPS (number of pictures/second). CuDNN version is 7.5, including data loading, network forward execution and post-processing, and Batch size is 1.
 
@@ -170,7 +170,7 @@ Please refer to [Model Zoo for PaddleYOLO](https://github.com/PaddlePaddle/Paddl
 
 Please refer to [YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov5)
 
-### YOLOv6
+### YOLOv6(v3.0)
 
 Please refer to [YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov6)
 
@@ -178,6 +178,10 @@ Please refer to [YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop
 
 Please refer to [YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov7)
 
+### YOLOv8
+
+Please refer to [YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov8)
+
 ### RTMDet
 
 Please refer to [RTMDet](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/rtmdet)
diff --git a/docs/feature_models/PaddleYOLO_MODEL.md b/docs/feature_models/PaddleYOLO_MODEL.md
index e63580a0aa8b91e3a8ed51213a31515d33fb70e3..eb7db710967294f2c26e9e01c300870fa5525bba 100644
--- a/docs/feature_models/PaddleYOLO_MODEL.md
+++ b/docs/feature_models/PaddleYOLO_MODEL.md
@@ -5,11 +5,12 @@
 ## 内容
 - [简介](#简介)
 - [模型库](#模型库)
-    - [PP-YOLOE+](#PP-YOLOE+)
+    - [PP-YOLOE](#PP-YOLOE)
     - [YOLOX](#YOLOX)
     - [YOLOv5](#YOLOv5)
     - [YOLOv6](#YOLOv6)
     - [YOLOv7](#YOLOv7)
+    - [YOLOv8](#YOLOv8)
     - [RTMDet](#RTMDet)
     - [VOC](#VOC)
 - [使用指南](#使用指南)
@@ -18,9 +19,10 @@
 
 ## 简介
 
-**PaddleYOLO**是基于[PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection)的YOLO系列模型库，**只包含YOLO系列模型的相关代码**，支持`YOLOv3`,`PP-YOLO`,`PP-YOLOv2`,`PP-YOLOE`,`PP-YOLOE+`,`YOLOX`,`YOLOv5`,`YOLOv6`,`YOLOv7`,`RTMDet`等模型，欢迎一起使用和建设！
+**PaddleYOLO**是基于[PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection)的YOLO系列模型库，**只包含YOLO系列模型的相关代码**，支持`YOLOv3`,`PP-YOLO`,`PP-YOLOv2`,`PP-YOLOE`,`PP-YOLOE+`,`YOLOX`,`YOLOv5`,`YOLOv6`,`YOLOv7`,`YOLOv8`,`RTMDet`等模型，欢迎一起使用和建设！
 
 ## 更新日志
+* 【2022/01/10】支持[YOLOv8](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8)预测和部署；
 * 【2022/09/29】支持[RTMDet](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet)预测和部署；
 * 【2022/09/26】发布[`PaddleYOLO`](https://github.com/PaddlePaddle/PaddleYOLO)模型套件；
 * 【2022/09/19】支持[`YOLOv6`](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6)新版，包括n/t/s/m/l模型；
@@ -28,7 +30,7 @@
 
 
 **注意:**
- - **PaddleYOLO**代码库协议为**GPL 3.0**，[YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov5),[YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov7)和[YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6)这3类模型代码不合入[PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection)，其余YOLO模型推荐在[PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection)中使用，**会最先发布PP-YOLO系列特色检测模型的最新进展**；；
+ - **PaddleYOLO**代码库协议为**GPL 3.0**，[YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov5),[YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6),[YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov7)和[YOLOv8](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8)这几类模型代码不合入[PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection)，其余YOLO模型推荐在[PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection)中使用，**会最先发布PP-YOLO系列特色检测模型的最新进展**；；
  - **PaddleYOLO**代码库**推荐使用paddlepaddle-2.3.2以上的版本**，请参考[官网](https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/install/pip/linux-pip.html)下载对应适合版本，**Windows平台请安装paddle develop版本**；
  - PaddleYOLO 的[Roadmap](https://github.com/PaddlePaddle/PaddleYOLO/issues/44) issue用于收集用户的需求，欢迎提出您的建议和需求。
  - 训练**自定义数据集**请参照[文档](#自定义数据集)和[issue](https://github.com/PaddlePaddle/PaddleYOLO/issues/43)。请首先**确保加载了COCO权重作为预训练**，YOLO检测模型建议**总`batch_size`至少大于`64`**去训练，如果资源不够请**换小模型**或**减小模型的输入尺度**，为了保障较高检测精度，**尽量不要尝试单卡训和总`batch_size`小于`32`训**；
@@ -36,7 +38,7 @@
 
 ## 模型库
 
-### [PP-YOLOE+](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/ppyoloe)
+### [PP-YOLOE](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/ppyoloe)
 
 <details>
 <summary> 基础模型 </summary>
@@ -147,13 +149,10 @@
 
 | 网络网络        | 输入尺寸   | 图片数/GPU | 学习率策略 | TRT-FP16-Latency(ms) |   mAP  |   AP50  | Params(M) | FLOPs(G) |  下载链接       | 配置文件 |
 | :------------- | :------- | :-------: | :------: | :---------: | :-----: |:-----: | :-----: |:-----: | :-------------: | :-----: |
-| YOLOv6-n       |  416     |    32      |   400e    |     1.0    |  31.1 |    45.3 |  4.74  | 5.16 |[model](https://paddledet.bj.bcebos.com/models/yolov6_n_416_400e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_n_416_400e_coco.yml) |
-| YOLOv6-n       |  640     |    32      |   400e    |     1.3    |  36.1 |    51.9 |  4.74  | 12.21 |[model](https://paddledet.bj.bcebos.com/models/yolov6_n_400e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_n_400e_coco.yml) |
-| *YOLOv6-t       |  640     |    32      |   400e    |     2.1    |  40.7 |    57.4 |  10.63  | 27.29 |[model](https://paddledet.bj.bcebos.com/models/yolov6_t_400e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_t_400e_coco.yml) |
-| *YOLOv6-s       |  640     |    32      |   400e    |     2.6    |  43.4 |    60.5 |  18.87  | 48.35 |[model](https://paddledet.bj.bcebos.com/models/yolov6_s_400e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_s_400e_coco.yml) |
-| *YOLOv6-m       |  640     |    32      |   300e    |     5.0    |  49.0 |    66.5 |  37.17  | 88.82 |[model](https://paddledet.bj.bcebos.com/models/yolov6_m_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_m_300e_coco.yml) |
-| *YOLOv6-l       |  640     |    32      |   300e    |     7.9    |  51.0 |    68.9 |  63.54  | 155.89 |[model](https://paddledet.bj.bcebos.com/models/yolov6_l_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_l_300e_coco.yml) |
-| *YOLOv6-l-silu  |  640     |    32      |   300e    |     9.6    |  51.7 |    69.6 |  58.59  | 142.66 |[model](https://paddledet.bj.bcebos.com/models/yolov6_l_silu_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_l_silu_300e_coco.yml) |
+| *YOLOv6-n       |  640     |    16      |   300e(+300e) |  2.0  |  37.5 |    53.1 |  5.07  | 12.49 |[model](https://paddledet.bj.bcebos.com/models/yolov6_n_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_n_300e_coco.yml) |
+| *YOLOv6-s       |  640     |    32      |   300e(+300e) |  2.7  |  44.8 |    61.7 |  20.18  | 49.36 |[model](https://paddledet.bj.bcebos.com/models/yolov6_s_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_s_300e_coco.yml) |
+| *YOLOv6-m       |  640     |    32      |   300e(+300e) |  -  |  49.5 |    66.9 |  37.74  | 92.47 |[model](https://paddledet.bj.bcebos.com/models/yolov6_m_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_m_300e_coco.yml) |
+| *YOLOv6-l(silu) |  640     |    32      |   300e(+300e) |  -  |  52.2 |    70.2 |  59.66  | 149.4 |[model](https://paddledet.bj.bcebos.com/models/yolov6_l_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_l_300e_coco.yml) |
 
 </details>
 
@@ -162,13 +161,10 @@
 
 | 网络模型     | 输入尺寸 | 导出后的权重(w/o NMS) | ONNX(w/o NMS)  |
 | :-------- | :--------: | :---------------------: | :----------------: |
-| yolov6-n |  416   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_416_400e_coco_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_416_400e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_416_400e_coco_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_416_400e_coco_wo_nms.onnx) |
-| yolov6-n |  640   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_400e_coco_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_400e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_400e_coco_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_400e_coco_wo_nms.onnx) |
-| yolov6-t |  640   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_t_400e_coco_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_t_400e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_t_400e_coco_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_t_400e_coco_wo_nms.onnx) |
-| yolov6-s |  640   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_400e_coco_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_400e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_400e_coco_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_400e_coco_wo_nms.onnx) |
-| yolov6-m |  640   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_wo_nms.onnx) |
-| yolov6-l |  640   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_wo_nms.onnx) |
-| yolov6-l-silu |  640   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_silu_300e_coco_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_silu_300e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_silu_300e_coco_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_silu_300e_coco_wo_nms.onnx) |
+| yolov6-n |  640   | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_300e_coco_w_nms.zip) &#124; [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_300e_coco_wo_nms.zip) | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_300e_coco_w_nms.onnx) &#124; [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_300e_coco_wo_nms.onnx) |
+| yolov6-s |  640   | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_300e_coco_w_nms.zip) &#124; [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_300e_coco_wo_nms.zip) | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_300e_coco_w_nms.onnx) &#124; [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_300e_coco_wo_nms.onnx) |
+| yolov6-m |  640   | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_w_nms.zip) &#124; [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_wo_nms.zip) | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_w_nms.onnx) &#124; [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_wo_nms.onnx) |
+| yolov6-l(silu) |  640  | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_w_nms.zip) &#124; [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_wo_nms.zip) | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_w_nms.onnx) &#124; [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_wo_nms.onnx) |
 
 </details>
 
@@ -208,6 +204,37 @@
 
 </details>
 
+
+### [YOLOv8](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8)
+
+<details>
+<summary> 基础模型 </summary>
+
+| 网络网络        | 输入尺寸   | 图片数/GPU | 学习率策略 | TRT-FP16-Latency(ms) | mAP<sup>val<br>0.5:0.95 | mAP<sup>val<br>0.5 | Params(M) | FLOPs(G) |    下载链接       | 配置文件 |
+| :------------- | :------- | :-------: | :------: | :------------: | :---------------------: | :----------------: |:---------: | :------: |:---------------: |:-----: |
+| *YOLOv8-n        |  640     |    16      |   500e   |    2.4   |  37.3  | 53.0 |  3.16   | 8.7 | [model](https://paddledet.bj.bcebos.com/models/yolov8_n_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8/yolov8_n_300e_coco.yml) |
+| *YOLOv8-s        |  640     |    16      |   500e   |    3.4   |  44.9  | 61.8 |  11.17  | 28.6 | [model](https://paddledet.bj.bcebos.com/models/yolov8_s_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8/yolov8_s_300e_coco.yml) |
+| *YOLOv8-m        |  640     |    16      |   500e   |    6.5   |  50.2  | 67.3 |  25.90  | 78.9 | [model](https://paddledet.bj.bcebos.com/models/yolov8_m_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8/yolov8_m_300e_coco.yml) |
+| *YOLOv8-l        |  640     |    16      |   500e   |    10.0   |  52.8  | 69.6 |  43.69  | 165.2 | [model](https://paddledet.bj.bcebos.com/models/yolov8_l_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8/yolov8_l_300e_coco.yml) |
+| *YOLOv8-x        |  640     |    16      |   500e   |    15.1  |  53.8  | 70.6 |  68.23  | 257.8 | [model](https://paddledet.bj.bcebos.com/models/yolov8_x_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8/yolov8_x_300e_coco.yml) |
+| *YOLOv8-P6-x     |  1280    |    16      |   500e   |    55.0  |    -   |   -  |  97.42  | 522.93 | [model](https://paddledet.bj.bcebos.com/models/yolov8p6_x_500e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8/yolov8p6_x_500e_coco.yml) |
+
+</details>
+
+<details>
+<summary> 部署模型  </summary>
+
+| 网络模型     | 输入尺寸 | 导出后的权重(w/o NMS) | ONNX(w/o NMS)  |
+| :-------- | :--------: | :---------------------: | :----------------: |
+| YOLOv8-n |  640   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_n_500e_coco_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_n_500e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_n_500e_coco_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_n_500e_coco_wo_nms.onnx) |
+| YOLOv8-s |  640   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_s_500e_coco_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_s_500e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_s_500e_coco_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_s_500e_coco_wo_nms.onnx) |
+| YOLOv8-m |  640   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_m_500e_coco_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_m_500e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_m_500e_coco_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_m_500e_coco_wo_nms.onnx) |
+| YOLOv8-l |  640   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_l_500e_coco_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_l_500e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_l_500e_coco_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_l_500e_coco_wo_nms.onnx) |
+| YOLOv8-x |  640   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_x_500e_coco_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_x_500e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_x_500e_coco_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_x_500e_coco_wo_nms.onnx) |
+
+</details>
+
+
 ### [RTMDet](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet)
 
 <details>
@@ -215,11 +242,11 @@
 
 | 网络网络        | 输入尺寸   | 图片数/GPU | 学习率策略 | TRT-FP16-Latency(ms) |   mAP  |   AP50  | Params(M) | FLOPs(G) |  下载链接       | 配置文件 |
 | :------------- | :------- | :-------: | :------: | :---------: | :-----: |:-----: | :-----: |:-----: | :-------------: | :-----: |
-| *RTMDet-t       |  640     |    32      |   300e    |    2.8   |  40.9 | 57.9 |  4.90  | 16.21 |[下载链接](https://paddledet.bj.bcebos.com/models/rtmdet_t_300e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet/rtmdet_t_300e_coco.yml) |
-| *RTMDet-s       |  640     |    32      |   300e    |    3.3   |  44.5 | 62.0 |  8.89  | 29.71 |[下载链接](https://paddledet.bj.bcebos.com/models/rtmdet_s_300e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet/rtmdet_s_300e_coco.yml) |
-| *RTMDet-m       |  640     |    32      |   300e    |    6.4   |  49.1 | 66.8 |  24.71  | 78.47 |[下载链接](https://paddledet.bj.bcebos.com/models/rtmdet_m_300e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet/rtmdet_m_300e_coco.yml) |
-| *RTMDet-l       |  640     |    32      |   300e    |    10.2  |  51.2 | 68.8 |  52.31  | 160.32 |[下载链接](https://paddledet.bj.bcebos.com/models/rtmdet_l_300e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet/rtmdet_l_300e_coco.yml) |
-| *RTMDet-x       |  640     |    32      |   300e    |    18.0  |  52.6 | 70.4 |  94.86  | 283.12 |[下载链接](https://paddledet.bj.bcebos.com/models/rtmdet_x_300e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet/rtmdet_x_300e_coco.yml) |
+| *RTMDet-t       |  640     |    32      |   300e    |    2.8   |  40.9 | 57.9 |  4.90  | 16.21 |[model](https://paddledet.bj.bcebos.com/models/rtmdet_t_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet/rtmdet_t_300e_coco.yml) |
+| *RTMDet-s       |  640     |    32      |   300e    |    3.3   |  44.5 | 62.0 |  8.89  | 29.71 |[model](https://paddledet.bj.bcebos.com/models/rtmdet_s_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet/rtmdet_s_300e_coco.yml) |
+| *RTMDet-m       |  640     |    32      |   300e    |    6.4   |  49.1 | 66.8 |  24.71  | 78.47 |[model](https://paddledet.bj.bcebos.com/models/rtmdet_m_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet/rtmdet_m_300e_coco.yml) |
+| *RTMDet-l       |  640     |    32      |   300e    |    10.2  |  51.2 | 68.8 |  52.31  | 160.32 |[model](https://paddledet.bj.bcebos.com/models/rtmdet_l_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet/rtmdet_l_300e_coco.yml) |
+| *RTMDet-x       |  640     |    32      |   300e    |    18.0  |  52.6 | 70.4 |  94.86  | 283.12 |[model](https://paddledet.bj.bcebos.com/models/rtmdet_x_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet/rtmdet_x_300e_coco.yml) |
 
 </details>
 
@@ -264,7 +291,6 @@
 | 网络模型        | 输入尺寸   | 图片数/GPU | 学习率策略 | TRT-FP16-Latency(ms) | mAP(0.50,11point) | Params(M) | FLOPs(G) |    下载链接       | 配置文件 |
 | :-----------: | :-------: | :-------: | :------: | :------------: | :---------------: | :------------------: |:-----------------: | :------: | :------: |
 | YOLOv5-s        |  640     |    16     |   60e    |     3.2   |  80.3 |  7.24  | 16.54 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov5_s_60e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/voc/yolov5_s_60e_voc.yml) |
-| YOLOv6-s        |  640     |    32     |   40e    |     2.7   |  84.7 |  18.87 | 48.35 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov6_s_40e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/voc/yolov6_s_40e_voc.yml) |
 | YOLOv7-tiny     |  640     |    32     |   60e    |     2.6   |  80.2 |  6.23  | 6.90 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov7_tiny_60e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/voc/yolov7_tiny_60e_voc.yml) |
 | YOLOX-s         |  640     |    8      |   40e    |     3.0   |  82.9 |  9.0   |  26.8 | [下载链接](https://paddledet.bj.bcebos.com/models/yolox_s_40e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/voc/yolox_s_40e_voc.yml) |
 | PP-YOLOE+_s     |  640     |    8      |   30e    |     2.9   |  86.7 |  7.93  |  17.36 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_s_30e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/voc/ppyoloe_plus_crn_s_30e_voc.yml) |
diff --git a/docs/feature_models/PaddleYOLO_MODEL_en.md b/docs/feature_models/PaddleYOLO_MODEL_en.md
index 46d3483589bf52b5874fd2c31f1adfd5d69af4b5..b73634759811e9f8854495ebe26a3e1ede23115b 100644
--- a/docs/feature_models/PaddleYOLO_MODEL_en.md
+++ b/docs/feature_models/PaddleYOLO_MODEL_en.md
@@ -5,11 +5,12 @@
 ## Introduction
 - [Introduction](#Introduction)
 - [ModelZoo](#ModelZoo)
-    - [PP-YOLOE+](#PP-YOLOE+)
+    - [PP-YOLOE](#PP-YOLOE)
     - [YOLOX](#YOLOX)
     - [YOLOv5](#YOLOv5)
     - [YOLOv6](#YOLOv6)
     - [YOLOv7](#YOLOv7)
+    - [YOLOv8](#YOLOv8)
     - [RTMDet](#RTMDet)
     - [VOC](#VOC)
 - [UserGuide](#UserGuide)
@@ -18,10 +19,11 @@
 
 ## Introduction
 
-**PaddleYOLO** is a YOLO Series toolbox based on [PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection), **only relevant codes of YOLO series models are included**. It supports `YOLOv3`,`PP-YOLO`,`PP-YOLOv2`,`PP-YOLOE`,`PP-YOLOE+`,`YOLOX`,`YOLOv5`,`YOLOv6`,`YOLOv7`,`RTMDet` and so on. Welcome to use and build it together!
+**PaddleYOLO** is a YOLO Series toolbox based on [PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection), **only relevant codes of YOLO series models are included**. It supports `YOLOv3`,`PP-YOLO`,`PP-YOLOv2`,`PP-YOLOE`,`PP-YOLOE+`,`YOLOX`,`YOLOv5`,`YOLOv6`,`YOLOv7`,`YOLOv8`,`RTMDet` and so on. Welcome to use and build it together!
 
 ## Updates
 
+* 【2023/01/10】Support [YOLOv8](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8) inference and deploy;
 * 【2022/09/29】Support [RTMDet](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet) inference and deploy;
 * 【2022/09/26】Release [`PaddleYOLO`](https://github.com/PaddlePaddle/PaddleYOLO);
 * 【2022/09/19】Support the new version of [`YOLOv6`](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6), including n/t/s/m/l model;
@@ -29,13 +31,13 @@
 
 
 **Notes：**
- - The Licence of **PaddleYOLO** is **GPL 3.0**, the codes of [YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov5),[YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov7) and [YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6) will not be merged into [PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection). Except for these three YOLO models, other YOLO models are recommended to use in [PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection), **which will be the first to release the latest progress of PP-YOLO series detection model**;
+ - The Licence of **PaddleYOLO** is **GPL 3.0**, the codes of [YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov5),[YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6),[YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov7) and [YOLOv8](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8) will not be merged into [PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection). Except for these three YOLO models, other YOLO models are recommended to use in [PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection), **which will be the first to release the latest progress of PP-YOLO series detection model**;
  - To use **PaddleYOLO**, **PaddlePaddle-2.3.2 or above is recommended**，please refer to the [official website](https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/install/pip/linux-pip.html) to download the appropriate version. **For Windows platforms, please install the paddle develop version**;
  - Training **Custom dataset** please refer to [doc](#CustomDataset) and [issue](https://github.com/PaddlePaddle/PaddleYOLO/issues/43). Please **ensure COCO trained weights are loaded as pre-train** at first. We recommend to use YOLO detection model **with a total `batch_size` at least greater than `64` to train**. If the resources are insufficient, please **use the smaller model** or **reduce the input size of the model**. To ensure high detection accuracy, **you'd better never try to using single GPU or total `batch_size` less than `32` for training**;
 
 ## ModelZoo
 
-### [PP-YOLOE+](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/ppyoloe)
+### [PP-YOLOE](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/ppyoloe)
 
 <details>
 <summary> Baseline </summary>
@@ -147,13 +149,10 @@
 
 | Model        | Input Size  | images/GPU | Epoch | TRT-FP16-Latency(ms) | mAP<sup>val<br>0.5:0.95 | mAP<sup>val<br>0.5 | Params(M) | FLOPs(G) |    download       | config |
 | :------------- | :------- | :-------: | :------: | :---------: | :-----: |:-----: | :-----: |:-----: | :-------------: | :-----: |
-| YOLOv6-n       |  416     |    32      |   400e    |     1.0    |  31.1 |    45.3 |  4.74  | 5.16 |[model](https://paddledet.bj.bcebos.com/models/yolov6_n_416_400e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_n_416_400e_coco.yml) |
-| YOLOv6-n       |  640     |    32      |   400e    |     1.3    |  36.1 |    51.9 |  4.74  | 12.21 |[model](https://paddledet.bj.bcebos.com/models/yolov6_n_400e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_n_400e_coco.yml) |
-| *YOLOv6-t       |  640     |    32      |   400e    |     2.1    |  40.7 |    57.4 |  10.63  | 27.29 |[model](https://paddledet.bj.bcebos.com/models/yolov6_t_400e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_t_400e_coco.yml) |
-| *YOLOv6-s       |  640     |    32      |   400e    |     2.6    |  43.4 |    60.5 |  18.87  | 48.35 |[model](https://paddledet.bj.bcebos.com/models/yolov6_s_400e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_s_400e_coco.yml) |
-| *YOLOv6-m       |  640     |    32      |   300e    |     5.0    |  49.0 |    66.5 |  37.17  | 88.82 |[model](https://paddledet.bj.bcebos.com/models/yolov6_m_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_m_300e_coco.yml) |
-| *YOLOv6-l       |  640     |    32      |   300e    |     7.9    |  51.0 |    68.9 |  63.54  | 155.89 |[model](https://paddledet.bj.bcebos.com/models/yolov6_l_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_l_300e_coco.yml) |
-| *YOLOv6-l-silu  |  640     |    32      |   300e    |     9.6    |  51.7 |    69.6 |  58.59  | 142.66 |[model](https://paddledet.bj.bcebos.com/models/yolov6_l_silu_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_l_silu_300e_coco.yml) |
+| *YOLOv6-n       |  640     |    16      |   300e(+300e) |  2.0  |  37.5 |    53.1 |  5.07  | 12.49 |[model](https://paddledet.bj.bcebos.com/models/yolov6_n_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_n_300e_coco.yml) |
+| *YOLOv6-s       |  640     |    32      |   300e(+300e) |  2.7  |  44.8 |    61.7 |  20.18  | 49.36 |[model](https://paddledet.bj.bcebos.com/models/yolov6_s_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_s_300e_coco.yml) |
+| *YOLOv6-m       |  640     |    32      |   300e(+300e) |  -  |  49.5 |    66.9 |  37.74  | 92.47 |[model](https://paddledet.bj.bcebos.com/models/yolov6_m_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_m_300e_coco.yml) |
+| *YOLOv6-l(silu) |  640     |    32      |   300e(+300e) |  -  |  52.2 |    70.2 |  59.66  | 149.4 |[model](https://paddledet.bj.bcebos.com/models/yolov6_l_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_l_300e_coco.yml) |
 
 </details>
 
@@ -162,13 +161,10 @@
 
 | Model     | Input Size | Exported weights(w/o NMS) | ONNX(w/o NMS)  |
 | :-------- | :--------: | :---------------------: | :----------------: |
-| yolov6-n |  416   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_416_400e_coco_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_416_400e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_416_400e_coco_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_416_400e_coco_wo_nms.onnx) |
-| yolov6-n |  640   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_400e_coco_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_400e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_400e_coco_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_400e_coco_wo_nms.onnx) |
-| yolov6-t |  640   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_t_400e_coco_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_t_400e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_t_400e_coco_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_t_400e_coco_wo_nms.onnx) |
-| yolov6-s |  640   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_400e_coco_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_400e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_400e_coco_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_400e_coco_wo_nms.onnx) |
-| yolov6-m |  640   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_wo_nms.onnx) |
-| yolov6-l |  640   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_wo_nms.onnx) |
-| yolov6-l-silu |  640   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_silu_300e_coco_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_silu_300e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_silu_300e_coco_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_silu_300e_coco_wo_nms.onnx) |
+| yolov6-n |  640   | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_300e_coco_w_nms.zip) &#124; [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_300e_coco_wo_nms.zip) | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_300e_coco_w_nms.onnx) &#124; [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_300e_coco_wo_nms.onnx) |
+| yolov6-s |  640   | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_300e_coco_w_nms.zip) &#124; [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_300e_coco_wo_nms.zip) | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_300e_coco_w_nms.onnx) &#124; [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_300e_coco_wo_nms.onnx) |
+| yolov6-m |  640   | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_w_nms.zip) &#124; [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_wo_nms.zip) | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_w_nms.onnx) &#124; [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_wo_nms.onnx) |
+| yolov6-l(silu) |  640  | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_w_nms.zip) &#124; [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_wo_nms.zip) | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_w_nms.onnx) &#124; [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_wo_nms.onnx) |
 
 </details>
 
@@ -209,6 +205,36 @@
 </details>
 
 
+### [YOLOv8](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8)
+
+<details>
+<summary> Baseline </summary>
+
+| Model        | Input Size  | images/GPU | Epoch | TRT-FP16-Latency(ms) | mAP<sup>val<br>0.5:0.95 | mAP<sup>val<br>0.5 | Params(M) | FLOPs(G) |    download       | config |
+| :------------- | :------- | :-------: | :------: | :------------: | :---------------------: | :----------------: |:---------: | :------: |:---------------: |:-----: |
+| *YOLOv8-n        |  640     |    16      |   500e   |    2.4   |  37.3  | 53.0 |  3.16   | 8.7 | [model](https://paddledet.bj.bcebos.com/models/yolov8_n_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8/yolov8_n_300e_coco.yml) |
+| *YOLOv8-s        |  640     |    16      |   500e   |    3.4   |  44.9  | 61.8 |  11.17  | 28.6 | [model](https://paddledet.bj.bcebos.com/models/yolov8_s_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8/yolov8_s_300e_coco.yml) |
+| *YOLOv8-m        |  640     |    16      |   500e   |    6.5   |  50.2  | 67.3 |  25.90  | 78.9 | [model](https://paddledet.bj.bcebos.com/models/yolov8_m_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8/yolov8_m_300e_coco.yml) |
+| *YOLOv8-l        |  640     |    16      |   500e   |    10.0  |  52.8  | 69.6 |  43.69  | 165.2 | [model](https://paddledet.bj.bcebos.com/models/yolov8_l_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8/yolov8_l_300e_coco.yml) |
+| *YOLOv8-x        |  640     |    16      |   500e   |    15.1  |  53.8  | 70.6 |  68.23  | 257.8 | [model](https://paddledet.bj.bcebos.com/models/yolov8_x_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8/yolov8_x_300e_coco.yml) |
+| *YOLOv8-P6-x     |  1280    |    16      |   500e   |    55.0  |    -   |   -  |  97.42  | 522.93 | [model](https://paddledet.bj.bcebos.com/models/yolov8p6_x_500e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8/yolov8p6_x_500e_coco.yml) |
+
+</details>
+
+<details>
+<summary> Deploy Models  </summary>
+
+| Model     | Input Size | Exported weights(w/o NMS) | ONNX(w/o NMS)  |
+| :-------- | :--------: | :---------------------: | :----------------: |
+| YOLOv8-n |  640   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_n_500e_coco_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_n_500e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_n_500e_coco_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_n_500e_coco_wo_nms.onnx) |
+| YOLOv8-s |  640   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_s_500e_coco_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_s_500e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_s_500e_coco_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_s_500e_coco_wo_nms.onnx) |
+| YOLOv8-m |  640   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_m_500e_coco_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_m_500e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_m_500e_coco_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_m_500e_coco_wo_nms.onnx) |
+| YOLOv8-l |  640   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_l_500e_coco_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_l_500e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_l_500e_coco_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_l_500e_coco_wo_nms.onnx) |
+| YOLOv8-x |  640   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_x_500e_coco_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_x_500e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_x_500e_coco_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_x_500e_coco_wo_nms.onnx) |
+
+</details>
+
+
 ### [RTMDet](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet)
 
 <details>
@@ -254,7 +280,6 @@
 | Model        | Input Size  | images/GPU | Epoch | TRT-FP16-Latency(ms) | mAP(0.50,11point) | Params(M) | FLOPs(G) |    download       | config |
 | :-----------: | :-------: | :-------: | :------: | :------------: | :---------------: | :------------------: |:-----------------: | :------: | :------: |
 | YOLOv5-s        |  640     |    16     |   60e    |     3.2   |  80.3 |  7.24  | 16.54 | [model](https://paddledet.bj.bcebos.com/models/yolov5_s_60e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/voc/yolov5_s_60e_voc.yml) |
-| YOLOv6-s        |  640     |    32     |   40e    |     2.7   |  84.7 |  18.87 | 48.35 | [model](https://paddledet.bj.bcebos.com/models/yolov6_s_40e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/voc/yolov6_s_40e_voc.yml) |
 | YOLOv7-tiny     |  640     |    32     |   60e    |     2.6   |  80.2 |  6.23  | 6.90 | [model](https://paddledet.bj.bcebos.com/models/yolov7_tiny_60e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/voc/yolov7_tiny_60e_voc.yml) |
 | YOLOX-s         |  640     |    8      |   40e    |     3.0   |  82.9 |  9.0   |  26.8 | [model](https://paddledet.bj.bcebos.com/models/yolox_s_40e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/voc/yolox_s_40e_voc.yml) |
 | PP-YOLOE+_s     |  640     |    8      |   30e    |     2.9   |  86.7 |  7.93  |  17.36 | [model](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_s_30e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/voc/ppyoloe_plus_crn_s_30e_voc.yml) |