Core Viewpoint - The article discusses the shift in the computing power market towards domestic solutions, highlighting the decline in profitability for NVIDIA products and the rise of domestic computing power projects supported by substantial subsidies [1][6][10]. Group 1: Market Dynamics - The computing power market is witnessing a transformation, with domestic solutions gaining traction as NVIDIA's products fail to maintain their previous popularity [2][4]. - Major internet companies are adapting to domestic chip solutions, indicating a collective industry shift towards supply chain security and business development needs [2][3]. - The domestic computing power projects are becoming commercially viable due to policy support and increasing market demand [3][10]. Group 2: Financial Support and Subsidies - Financial institutions are actively supporting domestic computing power projects, with significant subsidies available, reaching up to 80% of project costs [6][8]. - The government is providing targeted assistance to domestic computing power projects, including lowering funding barriers and offering substantial financial incentives [7][10]. - The cost of domestic computing power is becoming more competitive due to these subsidies, which help bridge the price gap with NVIDIA products [8][9]. Group 3: Technological Advancements - Domestic chip manufacturers have made significant advancements, achieving performance levels comparable to NVIDIA's mainstream products [12][16]. - The demand for inference tasks is expected to drive the growth of domestic computing power, with a notable increase in token usage for AI models [13][20]. - The development of supernode products is emerging as a key trend, enhancing efficiency and reducing costs in the deployment of AI infrastructure [26][27]. Group 4: Market Competition and Strategy - The domestic chip market is entering a competitive phase, with the need for rapid commercialization and efficient deployment becoming critical [25][30]. - Pricing strategies are evolving, with manufacturers willing to offer discounts to penetrate the market and expand application scenarios [28][29]. - The lack of a unified standard in the software ecosystem poses challenges for the adoption of domestic chips, highlighting the need for improved interoperability [29][30].

此前，上交所官网披露了沐曦股份科创板IPO首轮问询回复。作为国内领先的高性能通用GPU芯片设计 企业和"硬科技"代表，沐曦股份的IPO进程备受市场关注。在当前全球AI算力需求持续井喷，以及国家 持续加大对高端集成电路产业和人工智能核心技术政策支持的双重背景下，这一重要进展，既标志着沐 曦股份在推进产业化落地和进军资本市场方面迈出了坚实一步，也为国产高端算力芯片的发展注入了新 的活力。 AI竞速时代：算力需求的井喷与共振 自2022年底OpenAI发布chatgpt以来，市场见证了一场由AI引发的技术快速发展浪潮。AI大模型的快速 迭代所带来的人工智能能力大幅提升，以及多模态、智能体所带来的应用领域的不断拓展，都引发了对 AI算力需求的井喷式增长。北美四大云计算巨头(META、微软、谷歌、亚马逊)的资本开支(CAPEX)不 断加码体现出对算力的渴望：其资本开支从2023年的1500亿美元，到2025年预计将超过3000亿美元，两 年翻番。四巨头以空前力度加码AI数据中心建设，以应对愈演愈烈的算力"装备竞赛"。而作为这场浪潮 中的"卖铲人"，英伟达2026财年第一季度(截至2025年4月)数据中心业务收入同比大幅 ...