---
title: "CMST: The controlling subsidiary CMST Intelligent Transportation is considering drawing on the advanced architectural design of DeepSeek R1"
type: "News"
locale: "en"
url: "https://longbridge.com/en/news/228554790.md"
description: "CMST's holding subsidiary, CMST Intelligent Transportation, plans to draw on the advanced architectural design of DeepSeek R1 to build an integrated technology architecture that consolidates core capabilities such as knowledge base construction, code intelligent generation, and completion. The system will combine a self-developed small parameter inference model and a distributed multi-agent collaborative framework to form a hybrid intelligent system with knowledge sharing, task decoupling, and dynamic tuning capabilities, aimed at enhancing the cognitive decision-making ability and cross-scenario generalization level of logistics intelligent systems"
datetime: "2025-02-17T11:47:12.000Z"
locales:
  - [zh-CN](https://longbridge.com/zh-CN/news/228554790.md)
  - [en](https://longbridge.com/en/news/228554790.md)
  - [zh-HK](https://longbridge.com/zh-HK/news/228554790.md)
generator: "portal-rs"
---

# CMST: The controlling subsidiary CMST Intelligent Transportation is considering drawing on the advanced architectural design of DeepSeek R1

On February 17th, CMST stated on the interactive platform that its holding subsidiary, Zhongchu Zhiyun, is considering using DeepSeek as the foundational model to build an integrated technology architecture. This will deeply integrate its core capabilities such as knowledge base construction, code intelligent generation, and completion, while systematically drawing on the advanced architectural design of DeepSeek R1. By organically integrating its key technology modules with self-developed small parameter inference models and distributed multi-agent collaborative frameworks, it aims to form a hybrid intelligent system with knowledge sharing, task decoupling, and dynamic tuning capabilities, thereby continuously enhancing the cognitive decision-making ability and cross-scenario generalization level of the logistics intelligent system

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> **Disclaimer: This article is for reference only and does not constitute any investment advice.**