企业级大模型调用全景研究 State of GenAI：Foundational Model in Chinese Enterprise, 2025 FROST & SULLIVAN INSIGHT The contents of these pages are copyright © Frost & Sullivan. All rights reserved. frostchina.com 中国GenAI市场洞察系列 | 2025 GenAI 中国GenAI市场洞察 ◼ 目录 | 引言 | | -------------------------- | 03 | | --- | --- | --- | --- | | 章节1 | 中国企业级大模型发展综述 | -------------------------- | 05 | | 章节2 | 中国企业级大模型调用现状及趋势 | -------------------------- | 09 | | 章节3 | 中国企业级大模型调用行为分析 | -------------------------- | 15 | | 章节4 | 中国企业级大模型调研企业画像与方法 ...

Core Viewpoint - The recent surge in open-source AI models in China is reshaping the global AI landscape, with significant implications for technology influence and application acceleration, while also presenting challenges related to model iteration and compatibility costs [1][2][3]. Group 1: Open-source Model Surge - In the past two weeks, Alibaba's Tongyi Qianwen has released six open-source models, marking a resurgence in China's large model development, reminiscent of the "hundred model battle" of 2023 [1]. - The recent open-source wave has seen major Chinese companies, including Alibaba and Tencent, rapidly releasing new models, with China occupying nine out of the top ten spots in the Hugging Face open-source model ranking [2]. - The success of DeepSeek is viewed as a turning point, prompting more Chinese companies to adopt open-source strategies and focus on model optimization and iteration [2]. Group 2: Competitive Landscape - The latest rankings from Chatbot Arena show Alibaba's Tongyi Qianwen 3 surpassing several closed-source models, indicating a shift towards open-source dominance in China [4]. - The divergence in paths between open-source and closed-source models is evident, with Chinese companies embracing open-source while U.S. firms lean towards closed-source strategies [4][5]. - Open-source models are seen as a way for latecomers in the AI field to break the dominance of established players, allowing for rapid optimization and ecosystem development [5]. Group 3: Challenges and Concerns - The rapid iteration of open-source models has led to a phenomenon of "tuning internal competition" and homogenization, raising concerns about a lack of disruptive innovation [7][8]. - Developers face challenges with frequent updates and compatibility issues, leading to increased adaptation costs and potential innovation stagnation [8]. - Experts suggest the need for unified API standards and a focus on foundational research to avoid low-level repetitive construction and to foster genuine algorithmic breakthroughs [8].

以下文章来源于新熵 ，作者茯神 新熵 . 洞察商业变量，探寻商业本质。 将投中网设为"星标⭐"，第一时间收获最新推送 国内大模型的竞争规则变了。 来源丨 茯神 编辑丨 思原 来源丨 新熵 DeepSeek给AI大模型行业，免费赠送了一波国民级别的市场教育，却也平等地在先行者们头上，悬起了一把达摩克利斯之剑。 其中，AI"六小虎"之中的智谱就是一个缩影，智谱脱胎于清华大学知识工程研究室，素来有"国家队"之称。然而就在最近开始频频出现融资动作，10天 之内补充弹药达15亿人民币；可与此同时，组织震荡颇有加剧之势，从一线团队到高管大牛皆有波及。冰火两重天的态势，可谓是目前除了DeepSeek 之外，大多数大模型从业者们，真实写照的一个缩影。 2024年底，智谱曾以200亿元的估值，完成一轮30亿元人民币的融资，在这之后，包括杭州城投、上乘资本、华发集团等国资背景的资方快马加鞭地 赶到为其注资。 不过，也有风投人士对「新熵」分析，DeepSeek的横空出世还是对智谱的估值造成了一定负面影响，快速拿钱也可能是为了抢下已经出现上涨瓶颈的 相对高价。 与大开现金粮仓之门形成反差的是，智谱在团队规模和对外投资上呈现出收缩之势 ...

Core Viewpoint - The article discusses the paradox of open-source large models in the AI industry, questioning how these models can generate revenue despite being freely available. It emphasizes that profitability is essential for business operations and suggests various monetization strategies that can be employed by companies in this space [5][8][41]. Group 1: Open Source Models and Revenue Generation - Open-source models have become mainstream, but there is skepticism about their ability to generate revenue [4][7]. - Companies can monetize open-source models through several strategies, such as charging for usage rights of certain models [12][18]. - Successful examples from the open-source world, like Red Hat, illustrate that companies can provide paid solutions around open-source products [9][10]. Group 2: Monetization Strategies - Companies can charge for customized B2B model deployments, which is a significant revenue source [20][33]. - Selling computational power, as demonstrated by DeepSeek, is another viable revenue stream, with reported daily profits of $470,000 and a profit margin of 545% [22][23]. - Open-source products often generate more revenue from services rather than direct product sales, creating an ecosystem that supports monetization [28][30]. Group 3: Market Dynamics and Challenges - The AI industry is still evolving, and many companies are struggling to achieve profitability, with significant investments in GPU resources yielding limited returns [45]. - The article highlights that the current focus for AI companies should be on gaining attention and user engagement rather than immediate profitability [47]. - The competitive landscape necessitates that companies adopt open-source strategies to remain relevant and avoid being overshadowed by leaders like DeepSeek [47][48].