On the same trading day, although Apple's stock price fell by about 1.2%, according to AiCoin data, its market value reached approximately 5.03 trillion USD, once again reclaiming the top position globally; Nvidia's stock price fell by about 4.2%, resulting in a market value of approximately 4.93 trillion USD, overtaken by Apple. This is the second time after a brief swap at the end of July that this has occurred. On the surface, it appears to be a ranking game between two giants, but behind it is the market's collective questioning of "how much AI will cost and how long it can last": amidst concerns about AI expenditure, funds are more willing to view Apple as a relatively safe haven. Correspondingly, Anthropic disclosed almost 900 billion USD in future expenditure obligations in its IPO documents, primarily locked in long-term contracts for data centers, power, and GPUs, a figure that greatly exceeds the liabilities directly listed on the balance sheet; only investors patiently flipping to the notes will see the true cost structure. According to the Financial Times of the UK, OpenAI has also lowered its latest funding target by 10 billion USD, now seeking about 20 billion USD at a valuation of approximately 1.25 trillion USD, with the primary market starting to use more cautious chips to assess the story of "AI unicorns." At the same time, earlier geopolitical undercurrents continue to hum in the background: according to senior officials in the Gulf countries, the Trump administration had previously notified allies to prepare for a possible brief and intense strike against Iran on a certain November 4, after which the US shifted to pressuring Iran through a maritime blockade of its ports. The situation has been long stuck in a state of "applying pressure but not fully escalating." Against this macro backdrop, AI-related assets and broader risk assets are being repriced.
Apple Reclaims Market Value Crown: AI Hardware Boom Cools
In the latest trading day, both companies' stock prices fell in a corrective move: Apple's stock price fell by about 1.2%, but its market value still reached approximately 5.03 trillion USD, reclaiming the top position globally; Nvidia's stock price fell by approximately 4.2%, with a market value dropping to about 4.93 trillion USD, losing the top spot. This marks Apple's first return to the "market value crown" since its brief overtaking at the end of July, and in a cycle dominated by AI narratives, the repeated swapping of the top position itself is a visualization of fluctuating sentiment and expectations.
Amid the uncertainties brought by AI spending, market reports indicate that investors are beginning to prefer technology giants like Apple with more mature profit models and steadier cash flow, viewing them as relatively safe havens. In contrast, Nvidia had previously seen its market value soar on the wave of AI chips, but now a larger stock price correction is interpreted as a proactive cooling of the high growth pricing for AI hardware, reflecting that funds are stepping back from the "infinite expansion of computing power story" and are demanding verifiable profit paths and spending discipline, with risk appetite adjusting towards a more restrained direction.
Anthropic's Hidden 900 Billion Obligation Exposed
As funds start to re-evaluate the spending discipline of AI companies, a particularly eye-catching figure is thrown out by Anthropic in its IPO documents—total future spending obligations amounting to nearly 900 billion USD. The documents show that this is not traditional borrowing that has already occurred, but rather long-term leasing and procurement arrangements locked in around data centers, power, and GPUs, equivalent to securing years-ahead cabinet space, power load, and computing chips "in advance" and writing the future infrastructure costs into today's prospectus through contracts.
The problem is that this nearly 900 billion USD mostly falls under off-balance sheet commitments: they are buried in the latter half of the financial report in notes, far larger than the liabilities directly listed on the balance sheet that investors can see at a glance. To truly understand Anthropic's long-term payment rhythm regarding power, data centers, and GPUs, one must patiently review the disclosed notes and restore these leasing and procurement obligations item by item, which significantly raises the identification cost. In the current AI infrastructure arms race, such spending locked in through long-term contracts is both a chip for competing for computing power and electricity, and a fixed cost and risk exposure that will be unavoidable for many years to come, adding a layer of high-intensity leverage structure beyond the balance sheet for the entire track.
OpenAI Cuts Financing by 10 Billion USD: Valuation Myth Faces Reality Test
After Anthropic locked in a series of high expenditures with nearly 900 billion USD in long-term contracts for the future, another leading model company has begun to retreat on the capital side. According to the Financial Times of the UK, OpenAI has reduced its latest round of financing target by 10 billion USD, now seeking around 20 billion USD at a valuation of approximately 1.25 trillion USD. For a company previously viewed by the market as an "infinite growth story," stepping back from larger-scale financing is interpreted by many observers as a proactive test of its ability to handle reality, and related financing information is currently still disclosed from a single source, with the final amount and valuation trend still needing to be verified by subsequent trading results.
This choice of "taking less money but maintaining a very high valuation" reflects the primary market's more refined calculation of the betting rhythm on super high-valued AI assets—not that there will be no investment, but that it will no longer unconditionally renew the valuation myth. In the secondary market, concerns surrounding computing power, data centers, and electricity costs have already weighed on the pricing of tech stocks like Apple and Nvidia, with investors increasingly questioning the profit paths and timelines for these expenditures. OpenAI's tightening of its financing strategy appears to not be an isolated event but rather a concrete reflection of the same wave of "AI expenditure scrutiny" feedback between primary and secondary markets.
Recall Shutdown and Token Destruction: The Withdrawal of Crypto AI Narrative
As the primary and secondary markets begin to recalculate the profits and losses of the "computing power story," a clearing sample has also emerged in the on-chain world. The Recall Foundation recently announced that it will gradually cease operations related to its protocol and concentrate on disposing of existing chips on-chain, planning to destroy approximately 358.6 million RECALL tokens. This is not a sudden, accident-like termination but rather a proactive shutdown process initiated by the project team: the official clearly stated that the true adoption situation, ongoing operational costs, and expected growth curve of the protocol are no longer sufficient to support continued development and maintenance.
More importantly, this exit did not stem from hacker attacks or contract loopholes; the foundation deliberately emphasized that the decision belongs to operational considerations, not a passive security incident. This combination of "proactive shutdown + token destruction" signifies that some "AI Agent + Crypto" projects have begun to acknowledge the gap between commercial fundamentals and early narratives, allowing on-chain assets to be reclaimed through regulated destruction rather than drifting uncontrolled. Recall's choice reflects a transition in this track from the peak period of high-frequency conceptual creation and valuation seizing into a more cautious phase: teams and token holders must confront real usage scenarios and cost curves, and after the heat retreats, only AI + crypto projects capable of closing business loops have the reason to continue existing.
Geopolitical Tensions Coupled with AI Cooling: A New Turning Point for Risk Assets
According to senior officials in the Gulf countries, the Trump administration had requested Gulf allies to prepare for a possible brief and intense strike against Iran on a certain November 4, aiming to further destroy its nuclear program or force it to reach an agreement; after this warning, the US did not directly engage in military action, but continued to apply pressure on Iran through a maritime blockade of its ports. This geopolitical tension, which has not truly eased, provides a macro "tail risk" that could be activated for global risk asset pricing at any time. Against this backdrop, Apple's slight stock price adjustment overtakes Nvidia, with both companies' market values repeatedly swapping in the AI cycle, Anthropic revealing nearly 900 billion USD in long-term spending obligations in its IPO documents, OpenAI proactively reducing its financing target, and Recall choosing to shut down and destroy approximately 358.6 million tokens, all collectively outlining a theme: from technology blue chips to the primary market, to the "AI + crypto" track, AI-related risk assets are being repriced. What truly needs to be observed next is not the daily stock price or narrative heat, but whether the high long-term costs of AI infrastructure can be digested by commercial revenues, the financing progress of leading AI companies at more prudent valuations, the survival and exit paths of on-chain AI projects during the retreat period, and whether the ever-present geopolitical undercurrent will escalate at some point and rewrite the entire pricing framework of risk assets.
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