Opinion: Meta's sale of computing power may be intended to boost confidence in the company's valuation; we reiterate the investment opportunities in the neocloud sector.
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HTX DeepThink: Meta's sale of AI computing power raises concerns, marking a new phase in the generational differentiation of computing power assets.
Chloe (@ChloeTalk1), a columnist for HTX DeepThink and a researcher at HTX Research, points out that Meta's recent sale of some AI computing power has sparked concerns about an oversupply of computing power, putting pressure on GPU cloud service providers and the semiconductor sector. However, from the perspective of the actual situation in the industry chain, this change cannot be simply interpreted as the peak of AI computing power demand. It is more likely that computing power assets are beginning to show generational differentiation: the previous generation of GPUs and non-core computing resources are gradually shifting to commercial leasing, while new-generation high-performance clusters such as Blackwell and Rubin remain relatively scarce.
Industrial Securities: The news regarding Meta's external leasing and sales of computing power should not be interpreted overly pessimistically as a sign of computing power surplus.
According to Mars Finance, on Wednesday, news that Meta plans to sell its surplus AI computing power triggered a sharp correction in global AI hardware and high-flying technology stocks. Xingye Securities believes that the news regarding Meta's external leasing and sale of computing power should not be interpreted overly pessimistically as a surplus of computing power/a comprehensive slowdown in Capex, because (1) this is not new news; there were related reports in May of this year; (2) Meta is a special case among hyperscalers; its toC-oriented business means its AI monetization capabilities mainly rely on advertising, and its exploration of cloud business can improve shareholder returns and cash flow; (3) Meta still has a computing power gap; this week, it was just reported that Google restricted its access and Meta signed an agreement with Crusoe; (4) hardware demand comes from inference, not from inflation on the training side. (Cailian Press)
White-haired stock market guru Serenity agrees with Wells Fargo's view that Meta's sale of excess computing power is a signal of strong AI demand.
Odaily Odaily reports that Serenity, a well-known stock market commentator, posted on X agreeing with Wells Fargo's viewpoint, believing the market has completely misinterpreted Meta's statement regarding the sale of excess computing power. Wells Fargo stated that Meta's intention to sell excess computing power is a positive sign that underlying AI demand and unit economics remain strong. Wells Fargo noted, "While Meta is moving forward with this plan, we do not believe this means Meta will cut capital expenditures (CapEx), nor do we believe overall computing power demand has decreased." Wells Fargo believes that Neocloud's move further validates the huge opportunities in the AI infrastructure market and highlights the potential for industry consolidation, although Neocloud may face some competition in the future.
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.
Zuckerberg signals the commercialization of computing power, suggesting that Meta infrastructure may enter a dual-track model of "self-use + external leasing".
According to BlockBeats, on July 1st, Bloomberg reported that Mark Zuckerberg stated in a May shareholder call, "Almost every week, different companies come to us, either wanting us to build an API service or asking if we have computing power to sell to them, at a higher price than we paid. We haven't done that yet because we have our own need for that computing power," Zuckerberg said at the time. "But obviously, if we realize we've overbuilt, then that's an option, which partly gives us the confidence to invest in scaling up." In the rapidly evolving AI race, Zuckerberg has repeatedly stated that he believes the entire industry is facing a bottleneck in computing power, and that Meta should accumulate as much computing power as possible before deciding how to use it. Despite facing numerous complex challenges, Meta CEO Mark Zuckerberg has signaled to investors that he is willing to sell excess computing infrastructure and even launch so-called API services, allowing customers to pay based on AI usage—a business typically measured in "tokens" (i.e., the amount of data generated and consumed when a customer queries). Discussions surrounding Meta Platforms' potential commercialization of some of its AI computing power have raised concerns about a potential "oversupply" of computing power. However, analysts argue that this assessment is oversimplified. Meta currently does not have any significant surplus computing power available for sale. On one hand, it continues to expand its investment in AI infrastructure and has signed large-scale computing power agreements with companies like Crusoe. On the other hand, its existing H100/H200 resources are primarily used for internal recommendation systems and AI model training, and demand remains tight. Therefore, the so-called "selling computing power" is more of a future option for asset utilization than a current reality. Overall, it reflects a shift in AI computing power from a single scarcity to a multi-generational, tiered use and long-term capacity planning phase.
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.