如果你在12月5日早上中了摩尔线程的一签，恭喜你，在这个寒冷的冬天，你的账户里凭空多出了近28 万元。 作为"国产全功能GPU第一股"，摩尔线程在科创板的亮相堪称狂暴。发行价114.28元，开盘即暴涨 468%，股价一度冲高至688元，市值瞬间膨胀至2776亿元。这一刻，它不仅是科创板的明星，更是整个 A股积压已久的情绪宣泄口。 摩尔线程敲钟上市 但在满屏飘红的欢呼声中，作为理性的商业观察者，我们需要冷静地看一组略显冰冷、甚至有些刺眼的 数据：这家公司在2024年的营收为4.38亿元，而归属于母公司所有者的净利润是亏损16.18亿元。 一家年入仅4亿、亏损却高达16亿的公司，为何能撑起近3000亿的市值？如果你还在用传统的PE（市盈 率）去计算，你会觉得这个世界疯了。但在当下的A股，这恰恰证明了一件事： 中国硬科技资产的定价锚，已经从商业变现能力，彻底让位给了国家安全权重。 今天，我们就拨开K线图的迷雾，通过四个维度的深层拆解，看看这2700亿市值里，到底装的是泡沫， 还是黄金。 500倍的"市危率" 在投资圈，当一家公司没有利润时，我们看市销率（P/S）；当一家公司没有营收时，我们看市梦率。 而摩尔线程的出 ...

Group 1 - The article highlights the favorable policies and subsidies for domestic computing power, with subsidies reaching up to 60% for certain regions [2] - A city in the southwest has established a funding pool of 100 million yuan for domestic computing power projects, offering subsidies of 10%-15% based on construction costs [2] - The market for computing power leasing is also being driven by companies collaborating with major internet firms, indicating a strong push for domestic computing power projects [2] Group 2 - The rental price for computing power has significantly decreased, with a major company having spent 1.6 billion yuan on H800 servers, which are now facing a price drop [3][4] - The monthly rental price for H800 servers has nearly halved, leading to concerns that large companies may opt to terminate their leases due to lower cost-effectiveness [4] - The decline in rental prices is accelerating the turnover of server equipment, making lease termination a critical issue in the computing power market [4] Group 3 - The NVIDIA 4090 GPU is currently the most cost-effective option for leasing, priced around 7,000 yuan per month for an 8-card server [5] - The upcoming NVIDIA 5090 is expected to take time to surpass the 4090 in terms of market acceptance due to software compatibility issues [5] Group 4 - The Shanghai Lingang computing power project has streamlined its approval process, allowing project approvals to be completed within a week [7] - A company has delivered 1,057 B200 servers to a major firm in East China, with a total investment of approximately 4.25 billion yuan [8] Group 5 - Leading domestic chip manufacturers are employing strict regional management and reporting mechanisms to secure projects, limiting competition from other teams [9] - A domestic AI chip company has achieved significant revenue but operates with minimal visibility in the market, leading to misconceptions about its sales force [9] Group 6 - Japan's data centers are in high demand, surpassing those in Singapore and Malaysia, driven by stable resources and operational experience [11] - A major internet company has established a large H200 cluster in Japan, utilizing a strategy of contracting local integrators for project execution [11] Group 7 - The approval rate for IDC projects has dropped significantly, with some regions reporting only a 30% approval rate for applications submitted to national levels [13] - To navigate strict approval processes, some projects are adopting phased construction plans to avoid exceeding regulatory thresholds [14] Group 8 - The rental prices for IDC have decreased, with rates in prime areas dropping to around 200-300 yuan per kilowatt per month, leading to longer investment recovery times [16] - Despite the decline in rental prices, the market for data center REITs is booming, with subscription rates reaching 300-500 times for recent projects [16]

Core Viewpoint - The article discusses the competitive landscape of the AI inference chip market, particularly focusing on the domestic players in China and their strategies to challenge NVIDIA's dominance, especially the 4090 model, while navigating the complexities of cloud, edge, and on-device AI inference markets [2][4][16]. Group 1: AI Inference Market Dynamics - The demand for AI inference has surged due to the popularity of products like DeepSeek, leading to differing opinions on the future of edge versus cloud inference [2][3]. - There is a significant divide in opinions regarding the growth potential of edge AI inference, with some experts predicting a decline while others foresee continued growth [7][8]. - The AI inference market is characterized by a dual competition: domestic chips versus NVIDIA's 4090, and a strategic positioning battle for market share [4][16]. Group 2: Market Segmentation and Opportunities - The article outlines the definitions of cloud, edge, and on-device AI inference based on computational power, with a shift in boundaries due to advancements in large models [7]. - The traditional edge and on-device inference markets are described as saturated, with slow growth, while new applications driven by generative AI are emerging [11][14]. - The generative AI wave is expected to create new demand for edge AI chips, particularly in consumer electronics and smart hardware [14][15]. Group 3: Competitive Strategies - Domestic AI chip companies are focusing on achieving superior cost-performance ratios to compete with NVIDIA's offerings, particularly in specific application areas [4][17]. - The importance of software optimization and ecosystem partnerships is emphasized as critical for domestic companies to enhance their competitive edge [18][24]. - Companies are exploring various market segments, including the信创 market, healthcare, and energy, to find viable opportunities for AI chip deployment [22][23]. Group 4: Future Outlook - The article suggests that the competition among domestic AI chip manufacturers is just beginning, with upcoming products expected to leverage large memory and cost-performance advantages [26]. - The success of these companies will depend on their ability to establish deep partnerships with major clients and effectively navigate the evolving AI landscape [24][26].