Zuckerberg signals the commercialization of computing power, suggesting that Meta infrastructure may enter a dual-track model of "self-use + external leasing".
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Everbright Securities: Meta computing power leasing is a resource optimization method and does not change the medium-to-long-term expansion plan.
According to Odaily Odaily, Meta is venturing into external computing power leasing. A recent research report from Everbright Securities states that Meta's underlying logic for entering the cloud computing market is to create a new monetization channel for its massive AI infrastructure investments. This reflects that cloud computing is currently the fastest and most reliable way to recover huge upfront investments and improve current returns. It also indicates that the ability to monetize externally has become a cash flow guarantee for Meta to continue expanding its AI investments. Meta's overall plan to continuously increase its investment in AI computing power in the medium to long term has not changed. (Jinshi)
SemiAnalysis' latest report: Meta computing power procurement will accelerate, and capital expenditure may increase significantly next year.
According to Mars Finance, a recent report by semiconductor research firm SemiAnalysis emphasizes that computing power demand is far from peaking. The report points out that Meta's computing power construction will continue, predicting its capital expenditure next year will be astonishingly high, and the market need not worry about it cannibalizing the market share of new cloud competitors. SemiAnalysis analysis indicates that Meta's data center and computing procurement will accelerate, not slow down, and that Meta will become a significant source of revenue growth for new cloud companies such as CoreWeave and Nebius. (Cailian Press)
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.
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.
David Sacks strongly supports Palantir CEO's criticism of AI labs: True enterprise AI security lies in controlling one's own data, models, and computing power.
According to Beating, David Sacks, co-chair of the U.S. President's Council of Advisors on Science and Technology, published an article supporting Palantir CEO Alex Karp's sharp criticism of cutting-edge AI labs, stating that the mainstream media's portrayal of his interview as a "disastrous outburst" precisely demonstrates that Karp hit the nail on the head. Sacks points out that true "AI security" in a corporate environment is not abstract "alignment research" or government-led certification systems, but rather the ability to control one's own data, model weights, and computing power—preventing cutting-edge labs from "absorbing" a company's proprietary knowledge and turning it into the next product. He quotes Karp as saying, "They want to own their means of production, not hand them over to others." Sacks cites the conflict between Figma and Anthropic as a prime example: three days before the release of Claude Design, Anthropic's Chief Product Officer was still a member of Figma's board of directors, and Figma's founder stated that Anthropic "hadn't always been honest with them"; subsequently, Figma's stock price plummeted while Anthropic's valuation soared. He further listed products such as Claude Science, Claude Security, Claude Legal, and Claude Code, pointing out that Anthropic consistently targets vertical sectors originally served by companies that relied on its models, following a consistent pattern: "Observe where value is created first, then jump in." Sacks believes that the perception of open-source models as "dangerous" is not true for companies—retaining choice at the model layer and deciding who can use their core strengths is the real bottom line for corporate security. Previously, Palantir partnered with NVIDIA to deploy Nemotron's open AI models in sovereign environments, serving the US government and critical infrastructure customers, helping organizations train and deploy AI locally while maintaining complete control over data and intellectual property. Palanitir CEO Alex Karp recently gave a scathing interview on CNBC's "Squawk Box," criticizing leading AI model companies as "completely wrong" in their approach to selling AI. Karp emphasized that companies are currently dissatisfied with "cutting-edge labs" like OpenAI and Anthropic, believing they only pursue token maximization, wasting companies' time and money while handing over proprietary value and intellectual property. Karp stated that companies are "angry" and will strive to own their own AI production resources rather than relying on third parties. On June 29th, Palantir partnered with Nvidia to deploy Nvidia Nemotron open AI models in a sovereign environment, primarily serving the US government and critical infrastructure.
US computing power rental providers Nebius and CoreWeave turned positive in pre-market trading, shaking off the shadow of Meta's plan to build its own cloud business.
According to Mars Finance, on July 2nd, based on BIT (bit.com) market data, the pre-market share prices of US computing power leasing companies Nebius and CoreWeave turned positive, rising 3% and 2% respectively, after closing down 17% and 14% respectively yesterday. Yesterday's news that "Meta plans to build its own cloud business and sell surplus AI computing power" triggered a market-wide decline in computing power leasing companies.