SemiAnalysis' latest report: Meta computing power procurement will accelerate, and capital expenditure may increase significantly next year.
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SemiAnalysis: Meta will accelerate, rather than slow down, its computing power procurement; it is in talks with Anthropic to build its own AI model service platform.
According to BlockBeats, on July 3rd, SemiAnalysis stated in its latest report that after news broke that Meta might become a new Neocloud, the market's initial reaction was to sell off computing power cloud companies like CoreWeave and Nebius, and to renewed concerns about "AI computing power oversupply." However, the firm's assessment is the opposite: this concern may be wrong. Meta's data center and computing power procurement will not slow down, but rather continue to accelerate. The article mentions that in the first half of this year alone, Meta has already signed contracts for over 5GW of capacity in the cloud services and managed data center sectors, and this does not include its accelerating self-built projects. SemiAnalysis states that Meta is in final negotiations with Anthropic, hoping to obtain access to Claude private instances. If this comes to fruition, the significance goes beyond "Meta buying more computing power"; it suggests that Meta may be building its own AI model service platform. This model is somewhat similar to AWS's Bedrock, Microsoft's Foundry, and Google's Vertex. Meta can initially use Claude internally, or it can package the model capabilities as a token-as-a-service to provide services externally in the future. In the short term, it might use its own models externally and Anthropic models internally; in the long term, Meta might even incorporate Anthropic and OpenAI models into its external service system. SemiAnalysis states that the underlying logic is that Meta has computing power, advertisers, social network distribution capabilities, and consumer-end entry points. If it can combine cutting-edge models, intelligent agents, and sales and marketing SaaS, it will not just be a company that buys GPUs, but will be moving towards the upper layers of AI application and model distribution.
US pre-market news highlights: EDA giants focus on AI chip design; SpaceX officially included in the Nasdaq 100 index; Analysts say AI computing power demand is far from peaking.
Mars Finance reports the following key financial news from the US stock market that investors should pay attention to: 1. US stock index futures showed mixed results. Dow Jones futures rose 0.29%, S&P 500 futures fell 0.15%, and Nasdaq 100 futures fell 0.94%. 2. International oil prices rose slightly. WTI crude oil futures rose 0.61% to $68.967 per barrel; Brent crude oil futures rose 0.74% to $72.526 per barrel. 3. International gold and silver spot prices fluctuated narrowly. Spot gold rose 0.03% to $4166.01 per ounce; spot silver fell 0.64% to $61.62 per ounce. 4. European stock indices all fell. The UK FTSE 100 rose 0.47%, the French CAC 40 rose 0.20%, and the German DAX 30 fell 0.63%. 5. EDA giant Synopsys informed more than 10 chip manufacturers, including Samsung Electronics and SK Hynix, in April and May that it would "suspend" some of its wafer fab manufacturing analysis software, shifting resources to the more profitable AI chip design business. 6. SpaceX, owned by Elon Musk, was officially included in the Nasdaq 100 index today, becoming the first company in the index with a space business at its core. JPMorgan Chase estimates its weight in the index at approximately 1.3%. Wall Street generally gave it an "initial bullish" rating, with a target price as high as $800. 7. Google invested over €400 million in Proxima Fusion, a European nuclear fusion "unicorn" company, with the aim of building a commercial fusion power plant by the 2030s. 8. Anthropic announced a 20-year AI data center lease agreement with AI data center operator TeraWulf. The project has a capacity of approximately 401 megawatts and is expected to be operational in the second half of 2027, reaching full capacity in early 2028. 9. A recent report from semiconductor research firm SemiAnalysis indicates that AI computing power demand is far from peaking. The firm predicts that Meta computing power procurement will accelerate, and capital expenditure may increase significantly next year. 10. Walmart and its Sam's Club announced price reductions on thousands of popular summer items and everyday essentials across the United States. 11. Microsoft raised its Microsoft 365 Enterprise subscription fee earlier this month, with increases ranging from 8% to 33%. Personal and Education versions are currently unaffected. (Cailian Press)
Kingsoft Cloud accelerates GPU computing power construction, securing a 10 billion yuan budget from Xiaomi and a multi-billion yuan long-term contract from Alibaba.
According to a report by Jiemian News, as reported by Mars Finance, Kingsoft Cloud will accelerate the construction of its GPU computing power clusters in the second half of the year to meet the explosive growth in computing power demand from leading clients. Xiaomi's GPU computing power requirement for Kingsoft Cloud has been upgraded from a 10,000-GPU cluster, with the related budget increasing significantly from the initial nearly 4 billion yuan to over 10 billion yuan. In addition, Alibaba's big data model team has signed a 5-year computing power leasing contract with Kingsoft Cloud, involving more than 3,000 eight-GPU servers. Based on the contract price, the annualized revenue after full delivery will exceed 4 billion yuan. To meet the surging customer demand, Kingsoft Cloud has increased its 2026 capital expenditure plan to 15 billion yuan, with a full-year revenue target of 12.5 billion to 13.5 billion yuan. It is understood that due to tight upstream supply, Kingsoft Cloud is currently only accepting long-term contract customers for 3 to 5 years for its GPU computing power, and some orders are facing delivery delays. Due to concerns about the risk of asset impairment from stockpiling high-priced computing cards, Kingsoft Cloud is currently suspending its aggressive expansion of hardware, anticipating that computing hardware prices may reach a turning point in the third quarter of this year.
Did Meta "drag down" tech stocks? Industry insiders: Overcapacity in computing power is a misinterpretation.
According to Mars Finance, on July 2nd, A-share technology stocks plummeted, with semiconductors, computing hardware, and memory chips among the sectors experiencing significant declines. Taking the "Double Innovation Board," a major hub for technology stocks, as an example, the ChiNext Index and the STAR Market Composite Index fell by 5.71% and 5.64%, respectively. Market sentiment suggests the sharp drop in A-share technology stocks stemmed from the market's interpretation of Meta's sale of computing power as an indication of computing power surplus. However, many industry insiders believe this is a misinterpretation; Meta's sale of computing power does not signify the end of AI capital expenditure, but rather indicates the maturation of AI infrastructure business models. (Securities Times)
Meta's rental of computing power is similar to using existing resources to fund new ones, rather than ceasing the pursuit of high-end computing power.
According to Mars Finance, Meta is planning to launch a cloud computing business that leases computing power: one approach is to open up the model capabilities deployed on its own AI infrastructure to external customers, and the other is to lease out the more fundamental "raw computing power." However, the current situation seems more like Meta is using its existing, older computing power for cash flow recovery, rather than ceasing its pursuit of high-end computing power. In mid-to-late June, Meta was reported to have signed an agreement with Crusoe to acquire a total of approximately 1.6GW of AI computing capacity from two data centers in Texas and Missouri. Meanwhile, Meta raised its full-year capital expenditure guidance for Q1 2026 to $125-145 billion. Looking at these two events together, it seems more like a reallocation of resources across different generations and for different purposes: continuing to buy new GPUs to train cutting-edge models, but leasing out a portion of older GPUs (such as the H-series) used for high-traffic inference products and hosting external models, while not necessarily slowing down the purchase of the most scarce high-end GPUs. (Cailian Press)
UBS: Meta's sale of AI computing power may not be bad news; it could actually alleviate profit pressure.
According to BlockBeats, on July 2nd, UBS believes that Meta selling AI computing power or model access services to external customers should not necessarily be interpreted by the market as a negative signal of "AI infrastructure overcapacity." On the contrary, this could be a path for Meta to more quickly convert its massive AI investments into revenue. In its First Read report released on July 1st, UBS mentioned that Meta is reportedly considering two commercialization methods: selling "raw" computing power to external companies and providing access to AI models hosted on Meta's infrastructure. The report states that Zuckerberg has previously mentioned similar options publicly, so this is not entirely new information. However, this direction may still make some investors uneasy. Meta has previously described long-term growth opportunities to the market primarily including advertising, more immersive content experiences, business messaging, Meta AI, and AI devices, rather than directly becoming a cloud computing or computing power provider. Therefore, if the company does sell computing power externally, the market may question: Is this proactive monetization, or a passive digestion of excessive AI capital expenditure? UBS's assessment is more pragmatic. The bank believes that one of Meta's core problems is the excessively long investment cycle in AI, coupled with an unclear revenue realization timeline. Compared to waiting for Meta's AI chatbot or enterprise intelligent agent business to gradually scale up, selling cloud computing power or model access could potentially generate more immediate revenue, thus alleviating investor concerns about flat or even declining EPS in 2027. The report maintains its Buy rating on Meta with a 12-month target price of $865, while the listed share price is $601.85. UBS projects Meta's diluted GAAP EPS for 2026 and 2027 to be approximately $32.60 and $33.00, respectively, and states that it will not adjust its earnings forecast until the company confirms the relevant information. Its target price remains based on a 26x multiplier of its full-year diluted GAAP EPS forecast ending in Q1 2028. The significance of this report is that Meta's AI deals are entering a new phase: the market is no longer just asking how much it will spend on GPUs and data centers, but is beginning to demand to see how these investments will generate returns. For UBS, selling computing power is not a strategic retreat, but rather an additional cash flow outlet for its AI investment cycle.