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+# MiniCPM-V Best Practices
+
+**MiniCPM-V** is a series of end-side multimodal LLMs (MLLMs) designed for vision-language understanding. The models take image, video and text as inputs and provide high-quality text output, aiming to achieve **strong performance and efficient deployment**. The most notable models in this series currently include MiniCPM-Llama3-V 2.5 and MiniCPM-V 2.6. The following sections provide detailed tutorials and guidance for each version of the MiniCPM-V models.
+
+
+## MiniCPM-V 2.6
+
+MiniCPM-V 2.6 is the latest and most capable model in the MiniCPM-V series. With a total of 8B parameters, the model **surpasses GPT-4V in single image, multi-image and video understanding**. It outperforms **GPT-4o mini, Gemini 1.5 Pro and Claude 3.5 Sonnet** in single image understanding, and advances MiniCPM-Llama3-V 2.5's features such as strong OCR capability, trustworthy behavior, multilingual support, and end-side deployment. Due to its superior token density, MiniCPM-V 2.6 can for the first time support real-time video understanding on end-side devices such as iPad.
+
+* [Deployment Tutorial](https://modelbest.feishu.cn/wiki/C2BWw4ZP0iCDy7kkCPCcX2BHnOf)
+* [Training Tutorial](https://modelbest.feishu.cn/wiki/GeHMwLMa0i2FhUkV0f6cz3HWnV1)
+* [Quantization Tutorial](https://modelbest.feishu.cn/wiki/YvsPwnPwWiqUjlkmW0scQ76TnBb)
+
+## MiniCPM-Llama3-V 2.5
+
+MiniCPM-Llama3-V 2.5 is built on SigLip-400M and Llama3-8B-Instruct with a total of 8B parameters. It exhibits a significant performance improvement over MiniCPM-V 2.0.
+
+* [Quantization Tutorial](https://modelbest.feishu.cn/wiki/Kc7ywV4X1ipSaAkuPFOc9SFun8b)
+* [Training Tutorial](https://modelbest.feishu.cn/wiki/UpSiw63o9iGDhIklmwScX4a6nhW)
+* [End-side Deployment](https://modelbest.feishu.cn/wiki/Lwr9wpOQdinr6AkLzHrc9LlgnJD)
+* [Deployment Tutorial](https://modelbest.feishu.cn/wiki/LTOKw3Hz7il9kGkCLX9czsennKe)
+* [HD Decoding Tutorial](https://modelbest.feishu.cn/wiki/Ug8iwdXfhiHVsDk2gGEco6xnnVg)
+* [Model Structure](https://modelbest.feishu.cn/wiki/ACtAw9bOgiBQ9lkWyafcvtVEnQf)
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+# MiniCPM-V 最佳实践
+
+**MiniCPM-V**是面向图文理解的端侧多模态大模型系列。该系列模型接受图像和文本输入，并提供高质量的文本输出。自2024年2月以来，我们共发布了5个版本模型，旨在实现**领先的性能和高效的部署**，目前该系列最值得关注的模型包括：
+
+## MiniCPM-V 2.6
+
+MiniCPM-V系列的最新、性能最佳模型。总参数量 8B，单图、多图和视频理解性能**超越了 GPT-4V**。在单图理解上，它取得了优于 **GPT-4o mini、Gemini 1.5 Pro 和 Claude 3.5 Sonnet** 等商用闭源模型的表现，并进一步优化了 MiniCPM-Llama3-V 2.5 的 OCR、可信行为、多语言支持以及端侧部署等诸多特性。基于其领先的视觉 token 密度，MiniCPM-V 2.6 成为了首个支持在 iPad 等端侧设备上进行实时视频理解的多模态大模型。
+
+* [部署教程](https://modelbest.feishu.cn/wiki/LZxLwp4Lzi29vXklYLFchwN5nCf)
+* [训练教程](https://modelbest.feishu.cn/wiki/HvfLwYzlIihqzXkmeCdczs6onmd)
+* [量化教程](https://modelbest.feishu.cn/wiki/PAsHw6N6xiEy0DkJWpJcIocRnz9)
+
+## MiniCPM-Llama3-V 2.5
+
+MiniCPM-Llama3-V 2.5 基于 SigLip-400M 和 Llama3-8B-Instruct 构建，总共有 80 亿参数。其性能相比 MiniCPM-V 2.0 有了显著提升。
+
+* [量化教程](https://modelbest.feishu.cn/wiki/O0KTwQV5piUPzTkRXl9cSFyHnQb)
+* [训练教程](https://modelbest.feishu.cn/wiki/MPkPwvONEiZm3BkWMnyc83Tin4d)
+* [端侧部署](https://modelbest.feishu.cn/wiki/CZZJw1EDGitSSZka664cZwbWnrb)
+* [部署教程](https://modelbest.feishu.cn/wiki/BcHIwjOLGihJXCkkSdMc2WhbnZf)
+* [高清解码教程](https://modelbest.feishu.cn/wiki/L0ajwm8VAiiPY6kDZfJce3B7nRg)
+* [模型结构](https://modelbest.feishu.cn/wiki/X15nwGzqpioxlikbi2RcXDpJnjd)
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