从台积电上修指引：看 AI 算力需求趋势 20250718 摘要 台积电 2025 年第二季度财报超出预期，美元计价收入同比增长 17.8% 至 300.7 亿美元，毛利率达 58.6%，主要受益于 N3 制程平台放量和 N7 节点稼动率提升。未来业绩可能继续上修，因先进制程供不应求及潜 在涨价空间。 英伟达芯片的良率和新系列系统稳定性是影响 AI 算力需求的关键因素， 在供不应求的情况下，这些因素可能导致英伟达利润率提升，进而影响 整体市场规模。研究 AI 算力市场应聚焦大模型和应用变化，而非仅跟踪 产量数据。 台积电 N5 节点需求紧张，推动 N7 产能转移，提升了第二季度毛利率。 公司上调 2025 年全年收入指引至 30%，资本开支预期维持在 380 亿 至 420 亿美元。第三季度营收指引为 318 亿至 330 亿美元，毛利率维 持在 55.5%至 57.5%区间。 台积电预计第三季度毛利率受海外建厂进度加速和新台币升值影响，但 产品结构优化和先进制程提价可部分抵消负面影响。非 AI 领域市场需求 持续好转，工业及汽车领域逐步修复，而 AI 领域数据中心及 AI 加速器 需求持续旺盛。 Q&A 2 ...

Core Insights - The article reveals a fundamental challenge faced by the AI industry: the scarcity of computational resources [1] - It analyzes the contrasting strategies of DeepSeek and Anthropic in navigating this challenge [4][42] - The report emphasizes the importance of balancing technological breakthroughs and commercial success within limited computational resources [58] Group 1: AI Service Pricing Dynamics - AI service pricing is fundamentally a trade-off among three performance metrics: latency, throughput, and context window [2][3] - Adjusting these three parameters allows service providers to achieve any price level, making simple price comparisons less meaningful [30] - DeepSeek's extreme configuration sacrifices user experience for low pricing and maximized R&D resources [4][39] Group 2: DeepSeek's Market Performance - After the initial launch, DeepSeek experienced a significant drop in its own platform's user base, with a 29% decrease in monthly active users [15][12] - In contrast, the usage of DeepSeek models on third-party platforms surged nearly 20 times, indicating a shift in user preference [16][20] - The low pricing strategy of DeepSeek, at $0.55 per million tokens for input and $2.19 for output, initially attracted users but could not sustain long-term engagement [6][7] Group 3: Token Economics - Tokens are the fundamental units in AI, and their pricing is influenced by the service provider's ability to manage latency, throughput, and context window [21][22] - DeepSeek's official service has become less competitive in terms of latency compared to other providers, leading to a decline in its market share [33] - The context window offered by DeepSeek is the smallest among major providers, limiting its effectiveness in applications requiring extensive memory [34] Group 4: Anthropic's Resource Constraints - Anthropic faces similar computational resource challenges, particularly after the success of its programming tools, which increased demand for resources [44][45] - The API output speed of Anthropic's Claude has decreased by 30%, reflecting the strain on its computational resources [45] - Anthropic is actively seeking additional computational resources through partnerships with Amazon and Google [46][48] Group 5: Industry Trends and Future Outlook - The rise of inference cloud services and AI-driven applications is reshaping the competitive landscape, with a shift towards direct token sales rather than subscription models [51] - The article suggests that as affordable computational resources become more available, the long-tail market for AI services will continue to grow [52] - The ongoing price war among AI service providers is merely a surface-level issue; the deeper challenge lies in achieving technological advancements within resource constraints [58]

Core Insights - The article highlights the critical challenge faced by AI companies: the scarcity of computational resources, which is a fundamental constraint in the industry [1][5]. Pricing Dynamics - AI service pricing is fundamentally a trade-off among three performance metrics: latency, throughput, and context window [2][3]. - By adjusting these three parameters, service providers can achieve any price level, making simple price comparisons less meaningful [4][24]. DeepSeek's Strategy - DeepSeek adopted an extreme configuration with high latency, low throughput, and a minimal context window to offer low prices and maximize R&D resources [4][28]. - Despite DeepSeek's low pricing strategy, its official platform has seen a decline in user engagement, while third-party hosted models have surged in usage by nearly 20 times [16][20]. Competitive Landscape - Anthropic, another leading AI company, faces similar resource constraints, leading to a 30% decrease in API output speed due to increased demand [34][36]. - Both DeepSeek and Anthropic illustrate the complex trade-offs between computational resources, user experience, and technological advancement in the AI sector [5][53]. Market Trends - The rise of inference cloud services and the popularity of AI applications are reshaping the competitive landscape, emphasizing the need for a balance between technological breakthroughs and commercial success [5][45]. - The article suggests that the ongoing price war is merely a surface-level issue, with the real competition lying in how companies manage limited resources to achieve technological advancements [53].

以下文章来源于More Than Semi ，作者猫叔 More Than Semi . More Than SEMI 半导体行业研究 SemiAnalysis又来分析Deepseek了，在年初Deepseek刚刚爆火的时候，SemiAnalysis就出了一篇分析， 那篇写的内容确实很不错。 根据 Reuters（2025-05-29）的报道，DeepSeek 的低成本和短开发时间震惊了全球市场，导致美国科技 股价值蒸发数十亿美元，投资者重新评估 AI 巨头的估值。 这份报告深入探讨了DeepSeek R1及其在人工智能领域的竞争和市场动态，内容涵盖发布影响、技术进 步、用户使用趋势、token经济学、硬件限制、竞争格局等。先把原文的内容大概总结一下。 SemiAnal ysis原文总结 1. DeepSeek R1 的发布与市场影响 DeepSeek R1 自 2025 年 1 月 20 日推出已超过 150 天，其性能被认为与 OpenAI 的推理模型相当，但其 定价策略极具颠覆性：输入/输出token价格仅为 10 美元。这一低价策略震撼了全球 AI 市场，引发了广 泛讨论。许多人担心 DeepSeek ...