Citrini观点：英伟达护城河依然深厚，HBM4成本翻倍推升Rubin售价，高毛利与强定价权未受动摇
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Citrini analyst Jukan: MediaTek reportedly has secured Meta as an ASIC customer, following its TPU offerings.
According to a post on the X platform by Citrini analyst Jukan, Odaily Odaily, supply chain sources indicate that MediaTek has essentially secured a second ASIC customer besides Google. If all goes as planned, this customer will be Meta, previously rumored. MediaTek, as is customary, does not publicly comment on individual products, customer situations, or market rumors. While Qualcomm currently appears to have key customers such as Meta, Microsoft, and ByteDance, industry insiders believe that MediaTek's continued deepening of its cooperation with Google and its potential to secure a second customer puts it at a disadvantage. Semiconductor supply chain sources state that, considering the order prospects and generational transition pace of major cloud service providers for AI data centers and ASIC products, Google remains the most aggressive and proactive major customer. MediaTek not only has two products codenamed Zebrafish and Humufish, but according to market information and confirmation from industry insiders familiar with ASICs, its participation in the v9 generation Triggerfish is almost certain. This means that from the end of 2026 to 2028, and even into 2029, MediaTek can reliably receive revenue contributions from TPU mass production. Compared to Qualcomm's $15 billion cloud AI revenue target for 2029, it's only a matter of time before MediaTek, holding multiple TPU ASIC orders, reaches the $10 billion level. The industry is also focused on whether MediaTek can successfully secure its second major cloud service provider client. Based on earlier market information and recent supply chain confirmations, MediaTek is still actively collaborating with Meta on ASIC products, likely focusing on AI acceleration chips. Meta recently partnered with Arm and Qualcomm, but the products are all CPU-oriented, with no further concrete news regarding its self-developed AI acceleration chips. IC design industry insiders say that Meta's recent cloud AI development strategy has indeed been rather chaotic and unclear, with multiple adjustments to its internal chip development plans, seeking multiple partners and adopting different solutions in the CPU field alone. Regarding AI acceleration chips, although Meta has officially announced its collaboration with Broadcom, supply chain sources indicate that this has not interrupted the ongoing collaboration between MediaTek and Meta. IC design industry professionals also emphasized that MediaTek and Qualcomm's cloud AI development blueprints are still significantly different. MediaTek is concentrating all its resources on ASIC business, while Qualcomm plans to simultaneously promote customization and standardization, while also covering AI acceleration chips and CPU products.
Citrini analyst Jukan: Samsung Foundry achieved monthly profitability in June, its first since 2023.
According to a post on the X platform by Citrini analyst Jukan, as reported by Odaily Korean media, Samsung Foundry achieved monthly profitability in June, its first such month since 2023. With this positive profit in June, Samsung internally believes the likelihood of a profit turnaround starting in the third quarter has increased. The use of Samsung's 4nm process for HBM4 base dies is considered a key factor driving this turnaround, while improved yield rates are also seen as a major factor supporting the positive monthly profit. Industry sources estimate that Samsung's 4nm process yield has improved to approximately 80%.
Ministry of Human Resources and Social Security: By 2030, the large-scale model of the human resources and social security industry will be mature and complete, and the artificial intelligence application system will be basically sound.
According to Mars Finance, the Ministry of Human Resources and Social Security, the National Development and Reform Commission, the Ministry of Industry and Information Technology, and the National Data Administration recently jointly issued the "Implementation Opinions on Accelerating the Application and Development of 'Artificial Intelligence + Human Resources and Social Security'". A relevant official from the Ministry of Human Resources and Social Security answered reporters' questions regarding the "Implementation Opinions". In terms of promoting the work, a three-step work goal will be achieved within five years. First, building the foundation. Taking this year (2026) as a benchmark, the initial formation of the artificial intelligence application system, standard system, and guarantee system in the human resources and social security sector will be promoted. The infrastructure for "Artificial Intelligence + Human Resources and Social Security" applications will be deployed, a number of high-performance human resources and social security industry large-scale models and intelligent agent applications will be cultivated, and about 20 application scenarios based on human resources and social security industry large-scale models and corresponding high-quality datasets will be created, forming a collaborative development ecosystem of computing power, models, data, and scenario applications. Second, popularization and promotion. By 2027, a number of human resources and social security industry large-scale models and intelligent agents will be widely applied, and about 50 high-value application scenario empowerment paths will be explored, achieving significant results in intelligent development. Third, widespread application. By 2030, high-quality datasets will be effectively supplied, large-scale models for the human resources and social security industry will be mature and complete, and the artificial intelligence application system will be basically sound, forming an innovative landscape where artificial intelligence is widely applied in the human resources and social security sector. (Cailian Press)
SemiAnalysis: NVIDIA Delays or Adjustments to Multiple AI Rack-Scale Architectures, Limiting Rubin Ultra's Expansion Path
According to Mars Finance, on July 6th, SemiAnalysis reported that NVIDIA's latest rack-mount interconnect architecture, Kyber NVL144, has undergone a major adjustment just three months after its release, being delayed by more than 12 months to 2028. The main reason is the ongoing challenges in PCB planar design regarding manufacturing feasibility. Simultaneously, the NVL72x2 back-to-back rack architecture has been cancelled. This solution was originally intended to enhance the scalability of pure copper NVLink by deploying two Oberon racks back-to-back, but its complex structure and high operational burden on hyperscale cloud providers (CSPs) led to strong market skepticism and its eventual abandonment. Furthermore, due to the immaturity of CPO (Co-packaged Optics) technology, NVIDIA's larger-scale scaling solutions based on CPO NVSwitch (such as NVL576) may also continue to be delayed, or limited to small-batch trial production. This means that NVIDIA lacks a stable large-scale scale-up solution until CPO matures. Furthermore, the Rubin Ultra product roadmap has also changed: the originally planned "four-computing-chip" version has been cancelled, with only a "dual-computing-chip" version remaining, and the overall system-level performance is expected to drop to about half of the original solution. These adjustments mean that Nvidia's scale-up capabilities in the Rubin Ultra generation are limited. With the CPO NVSwitch unable to be deployed before the Feynman architecture, competitors such as the AMD MI500X or Google TPU v8i may have a relative window of opportunity in terms of scaling capabilities for large-scale training clusters. Meanwhile, Nvidia is expected to fill market demand during the product transition period and maintain overall supply chain pacing by shipping large quantities of Oberon Rubin racks and their "Ultra" versions.
JPMorgan Chase: Large-scale model usage and GPU leasing prices rise simultaneously, continuing to support AI infrastructure demand.
According to Mars Finance, JPMorgan Chase's latest "Data Center Watch" report shows that in June, large model usage, API spending, and non-cloud vendor GPU leasing prices all strengthened, indicating that demand for AI infrastructure is still expanding. Although model token prices continued to decline year-on-year, the increase in usage has significantly offset the impact of price reductions, and the overall unit economics of model providers are showing an improving trend. (Cailian Press)
Goldman Sachs maintains Nvidia's $285 price target, valuation already reflects ASIC market share risk.
According to BlockBeats, on July 7th, Goldman Sachs maintained its "Buy" rating and $285 price target for Nvidia, stating that the stock's current valuation already largely reflects the risk of market share loss due to its self-developed AI chips and increased competition. Nvidia has recently underperformed the broader semiconductor sector. While chip stocks generally rebounded on Monday, Nvidia's gains were limited; year-to-date, its performance has also significantly lagged behind AI hardware companies like Micron, AMD, Intel, and Marvell. The main market concern is that major customers like Alphabet and Amazon are pushing their self-developed ASIC chips to third parties while still purchasing Nvidia GPUs. Meanwhile, increased CPU investment in AI workloads is also giving AMD and Intel more growth opportunities. However, Goldman Sachs analyst James Schneider believes that Nvidia's risk discount is already too large. He expects that even with some market share gained by ASICs and some incremental growth from competitors, Nvidia's revenue could still achieve strong growth next year. The Vera Rubin platform, which will enter mass production in the second half of the year, will be key to determining whether the company can widen the performance gap again.