The launch of Meta's personal AI agent Muse, which surpassed 2.5 million downloads within six days and topped Apple's US App Store free chart, has sent ripples through the global AI stock pool—AMD surged past the $1 trillion market cap mark on Monday, joining forces with Meta, Intel, and Arm in a rare "CPU rally." On the surface, this appears to be a sector-wide celebration driven by a single hit product, but in essence, it reflects the market's repricing of a structural shift in computing power as AI transitions from "generation" to "action." Major financial institutions including Wedbush, Morgan Stanley, Goldman Sachs, and Jefferies have formed a systematic view: as AI agents move toward mass adoption, the computing bottleneck is shifting from GPUs to CPUs and memory, opening up tens of billions of dollars in incremental growth for the server CPU market.

The Muse phenomenon ignites chip stock sentiment

Meta's personal AI agent Muse, launched on September 8, surpassed 902,000 downloads within its first six days, beating the 773,000 downloads of its predecessor Meta AI during the same period, and quickly climbed to the top of Apple's US App Store free chart where it remained for several consecutive days. According to Sensor Tower data, Muse's cumulative downloads have exceeded 2.5 million, ranking ahead of ChatGPT and Claude. The initial consumer traction of Muse has fueled expectations of surging computing demand following the mass adoption of AI agents, driving significant capital flows into chip stocks such as AMD, Intel, and Arm. Catalyzed by this momentum, AMD jumped nearly 10% on Monday to $615.52, with its market value breaking through $1 trillion for the first time, making it the fourth US chip company to cross that threshold after Nvidia, Broadcom, and Micron. Meta shares surged 11%, Intel soared over 12%, and Arm skyrocketed more than 17%, while the Philadelphia Semiconductor Index closed up 4.3%—its biggest single-day gain since August 4—marking a fifth consecutive day of gains. South Korean chipmakers Samsung Electronics and SK Hynix saw their shares rise about 3.5% in early trading, and Taiwan's weighted index climbed 1.8% to a record high.

Gary Tan, portfolio manager at Allspring Global Investments, said the rally in Taiwan's market "reflects a growing belief that as AI adoption accelerates, hyperscalers will continue to expand their in-house chip capabilities." "If a product like Muse gains traction, hyperscalers will need more compute capacity, further accelerating demand for custom AI chips and supporting Taiwan's ASIC ecosystem," Tan added. This strong debut helps restore confidence in the AI trade, which had been weighed down by concerns over stretched valuations and, more recently, existential threats posed by advanced models. "The market quickly realized this is not just a product success story—it's a repricing of structural AI computing demand. Muse's mass adoption could significantly boost demand across the entire AI infrastructure supply chain, making chipmakers key beneficiaries of this trend," said Dilin Wu, strategist at Pepperstone.

How agent workflows elevate the CPU's role

The market's excitement centers not on the short-term ranking of an app but on how Muse represents AI agents fundamentally altering the underlying structure of computing demand. Traditional chatbots follow a workflow of "user asks—model generates answer—task ends," while agents operate in a continuous loop of "user sets a goal—model breaks down a plan—calls browsers and tools—executes operations—adjusts upon obstacles—continues execution." Within this loop, GPUs handle model inference and matrix operations, while CPUs shoulder heavy execution-layer workloads including task orchestration, virtual machine operations, browser control, API calls, database reads and writes, and sandbox security isolation. As Fujitsu described in its Hot Chips 2026 technical showcase, orchestration, retrieval, database calls, and conditional branching increasingly fall on CPUs, with GPUs handling only the batch matrix operations within those steps. The quantitative significance of this shift lies in the changing CPU/GPU ratio. Traditional training-oriented servers commonly use a 1:4 or even 1:8 CPU-to-GPU ratio, whereas agent inference emphasizes high concurrency and tool invocation, potentially pushing the CPU share toward a 1:1 to 1:2 range, with some institutions projecting even higher ratios.

Wall Street's structural thesis: formed but unverified in transmission

Around this structural shift, major Wall Street banks are converging on an increasingly clear consensus. Wedbush analyst Matthew Bryson put it most directly: "The only two manufacturers of meaningful computing devices for AI agents are Intel and AMD." This assessment pulls the server CPU market back into the core focus of AI investment. Jefferies analyst Jacky He also noted that as AI agents gain broader consumer adoption, higher inference and orchestration loads will directly benefit server CPU demand, emphasizing the profound significance of this trend for the long-overlooked x86 ecosystem. Morgan Stanley's assessment is more systematic. The bank estimates that agentic AI could add $32.5 billion to $60 billion in incremental value to the data center CPU market by 2030, a market already exceeding $100 billion. Morgan Stanley's core argument is that "the computing bottleneck is shifting from GPU to CPU and memory," and that AI's transition from a generation phase to an autonomous action phase will drive a structural leap in general-purpose computing intensity. Its research team further noted that when AI workloads shift from one-off inference to continuous task execution, CPU orchestration and coordination functions will become more strategically valuable than GPU raw compute power. JPMorgan adds an industry-structure perspective, arguing that the rise of AI agents will accelerate the rebalancing between custom chips and general-purpose CPUs at hyperscalers—increasing investment in both ASICs and custom accelerators while boosting demand for high-core-count server CPUs, with the two serving as complementary rather than substitute technologies. Citi's analyst team emphasized the "second-round beneficiaries" logic in its latest report—as CPU loads rise, supporting components such as DDR5 memory, enterprise SSDs, and high-bandwidth memory controllers will see demand pull-through, providing a tailwind for memory makers like Micron, Samsung Electronics, and SK Hynix.

It must be clarified, however, that the current rally retains a distinctly sentiment-driven character. Some analysts point out that this upswing is built on a "transmission chain with no disclosed orders yet." Oppenheimer analyst Jason Helfstein's calculation offers a sobering reference: Meta would need approximately 115 million paid Muse subscribers (at $20 per month) to generate roughly $27.5 billion to $28 billion in annualized AI agent revenue, a scenario he deems "unlikely" given uncertain paid conversion rates, intense competition, and low consumer trust in sharing passwords with Meta.

Ripple effects across the industry chain and cracks in the Meta celebration

If the structural uptick in CPU demand holds, beneficiaries will extend beyond the CPU duopoly. Meta is AMD's second-largest customer, contributing roughly 5.5% of its revenue, and the two companies expanded their partnership in February, planning to deploy up to 6 gigawatts of AMD Instinct GPUs. Arm also occupies a critical position in data center CPU architectures in the agent era. Looking deeper, ASIC custom chips, optical communications, and memory are all poised to benefit from the changing computing structure. But Meta's own financial health is bearing the cost of its AI investments. In the second quarter of 2026, Meta posted revenue of $60.8 billion, up 28% year over year, yet free cash flow plunged 91% from $8.55 billion in the same period last year to just $784 million; operating margins contracted from 43% to 31%, with full-year capital expenditure guidance reaching as high as $130 billion to $145 billion. Additionally, Amazon has blocked Muse from accessing its retail website, citing concerns that the agent failed to disclose its identity, may have attempted to obtain user credentials, and scraped account data—underscoring the escalating battle among platforms for control over user relationships in the agent era. The Meta Connect conference, opening Wednesday, will serve as the first key test of the sustainability of this "CPU rally." If Muse's user growth and monetization path receive further validation at the event, the market's repricing of AI inference computing architecture will gain a stronger anchor; conversely, the current valuation expansion driven by a single product catalyst may require a longer digestion period.