Meta's AI agent Muse hits 2.5M downloads in two weeks, stock surges 11.43%

The Muse Phenomenon: A $193 Billion Rally in One Day

On Tuesday evening, tech giant Meta staged a dramatic stock surge, soaring 11.43% in a single day and adding $193.8 billion (approximately ¥1.29 trillion) to its market capitalization. On the same day, AMD also jumped nearly 10%, pushing its market value above the $1 trillion mark for the first time.

The catalyst for this market frenzy? Muse — a personal AI agent that has topped the U.S. App Store's free charts with over 2.5 million downloads in just two weeks.

Yet, while capital markets celebrated, e-commerce giant Amazon blocked Muse from its platform, citing privacy and security risks. The agent, capable of price comparison and shopping assistance, was effectively shut out of a core commercial ecosystem.

The market's selective focus on the narrative — ignoring the rejection — raises a critical question: Has Muse truly ignited a new phase in AI trading?

01 A New Narrative for the Nasdaq

For those tracking Meta's Muse, mark your calendars: Meta Connect 2026 kicks off at 7:00 AM ET on September 24, where further announcements are expected.

Muse represents a significant departure from previous conversational agents. It is no longer a simple chatbot but a super agent capable of executing complex workflows autonomously:

• Sending and receiving emails
• Booking travel itineraries
• Filling out forms
• Cross-platform product price comparison
• Automated subscription renewal checks

More critically, Muse possesses cross-app memory and long-context association capabilities. It is already embedded directly into Meta AI, WhatsApp, Instagram, and Facebook, giving it seamless access to the daily workflows of billions of global users within days of launch.

The Hardware Revolution Behind the Hype

What truly excites investors is the disruptive AI hardware architecture underpinning Muse.

Traditional chatbots rely on GPUs for text token inference — computation ends when the user closes the browser. AI agents, however, involve:

• Extensive task orchestration
• Tool calls and API requests
• Environmental sandboxes
• State memory management
• Multi-round task execution loops

These processes are highly dependent on CPU computing power.

Two Interlocking Market Narratives

Muse's explosive popularity has generated two parallel yet interconnected logic chains in capital markets:

1. A new narrative for the market — Why the market needs this story, how to understand Muse, and how to form expectation gaps and investment labels.
2. Hardware entity growth — Identifying new resource consumption in the supply chain, which hardware components benefit, and where supply-demand gaps and price increases emerge.

Currently, the only AI demand that has truly been validated is coding. But with only about 30 million programmers globally, the paid user ceiling is visible.

Muse's personal agent targets billions of ordinary consumers — shifting the demand base from tens of millions to billions. The ceiling and computing power requirements are unprecedented. Personal agents are now seen as the second growth curve after coding, and Muse's success provides real data validation.

This narrative ripples through the semiconductor supply chain, pulling in upstream manufacturing.

The CPU Renaissance

The collective rally in chip stocks reflects a market realization: AI computing demand is evolving from "GPU-only" to "CPU + GPU collaborative" architecture. Server CPU value is undergoing a systemic revaluation.

Key drivers:

• Virtual machine management, OS residency, memory scheduling, and headless browser launches are all CPU-intensive
• Server CPUs are transitioning from supporting roles to core execution units for agents
• Complex workflows require sustained multi-round tool calls and long-cycle memory management, increasing pressure on KVCache capacity and memory bandwidth
• This directly boosts demand for HBM, DRAM, and NAND storage

Additionally, server CPUs are the largest end-use application for ABF substrates. However, the three global substrate leaders (Ibiden, Unimicron, Samsung Electro-Mechanics) are operating at full capacity, with resources prioritized for GPU giants like Nvidia and Google. This has left Intel and AMD facing a supply-demand gap exceeding 50% for CPU substrates.

On the supply side:

• TSMC plans a 10% price increase for foundry services
• AMD plans a 10% chipset price hike in Q4 2026
• Intel has reportedly raised P-core CPU prices by 10%, meeting only 50% of demand

While these price increases and shortages are fundamentally driven by semiconductor capacity cycles and wafer foundry pricing power — not directly by Muse's popularity — the market has conveniently absorbed them as evidence of a "full CPU chain shortage."

But does this logic seamlessly replace coding as the next AI trading theme? And can it deliver even greater returns?

02 Premature Revaluation

The Nasdaq's two-day rally suggests Wall Street is buying into this narrative. However, this surge appears more like a risk appetite rebound in a loose macroeconomic environment — capital pricing a hypothesis, not a realized outcome.

The market is now re-evaluating a scenario:

When truly practical personal AI agents require long-term residency in virtual machines, continuously consuming CPU, memory, and storage resources, and when user scale expands from millions to hundreds of millions or even billions, hardware demand could see a new explosion.

But returning to fundamentals, several points require gradual validation:

1. Downloads ≠ Active Users

While Muse's 2.5 million downloads in 13 days is impressive, Sensor Tower data shows its daily active users (DAU) on September 18 were only 448,000.

For Meta's billions of users, this is negligible. Moreover, Meta has not yet disclosed:

• Day-1 or week retention rates
• Clear subscription pricing

Downloads only reflect reach through Meta's powerful distribution channels. Retention rates determine the actual lifecycle of cloud virtual machines. In modern cloud-native architectures, if users stop interacting, the system triggers elastic scaling mechanisms, reclaiming idle Linux containers and compute nodes in milliseconds.

Without high retention, backend vCPU usage and memory bandwidth consumption will drop sharply. Without sustained resource consumption, the grand narrative of restructuring the CPU foundation will never translate into upstream orders.

2. Timing Gap: Pricing vs. Orders

Although Meta — as AMD's second-largest customer (contributing approximately 5.5% of revenue) — helped push AMD's market cap past $1 trillion, there is no public information confirming that Muse's virtual machine consumption will generate significant new procurement orders for AMD.

Only when AMD can demonstrate server CPU order growth exceeding expectations will this logic shift from speculation to realization.

3. Fragile Hardware Fundamentals

The underlying hardware market is actually quite fragile:

• Global PC shipments are projected to decline from 260 million units in 2026 to 250 million in 2027
• Intel's Q2 client revenue growth was driven mainly by average selling price (ASP) increases, not volume expansion

Connecting these dots reveals a market in a suspended state. When stock prices are pushed to historic highs in days, the market is pricing a "new world" — one requiring:

• Extremely fast agent penetration
• Exponential growth in user computing power and token consumption
• Cloud providers continuously increasing hardware spending

If any link in this chain breaks, the story could reverse:

• User novelty fades, agent penetration stalls
• Backend computing consumption growth slows
• Cloud providers realize poor ROI and cut capital expenditure (CapEx)
• Upstream component procurement shrinks

When that happens, it's not just the narrative that gets deflated — it's the stock prices.

03 What Conditions Are Needed?

The skepticism above points to what truly determines whether this AI story succeeds: computing architecture, traffic gateway ownership, and macro capital pricing rules.

The Core of Task-Based Agents

Task-based agents are essentially "OS-resident + environment sandbox scheduling." When agents need to maintain multi-round tool calls and long-cycle memory management, KVCache capacity and memory bandwidth pressure rises exponentially.

This shifts the value center of computing architecture, breaking the "GPU-only" dogma and bringing standard x86 or Arm CPUs back to center stage.

The Real Prize: Traffic Control

But what truly drove Meta's nearly $200 billion single-day market cap gain is the redistribution of internet traffic governance.

Previously, AI commercialization was largely limited to tens of millions of programmers. Muse's explosion showed the market the massive ceiling of agents targeting billions of consumers.

Amazon's wariness is telling: if agents can complete cross-platform price comparison and ordering, traditional e-commerce platforms would be stripped of their traffic gateways, reduced to mere logistics providers. Meanwhile, Shopify chose to integrate Muse because it lacks an exclusive gateway — integration means an additional sales channel.

So, what should be revalued is not just computing power. The core commercial moat of consumer-grade agents lies in absolute control over user workflows and transaction pathways.

The Monetization Gap

Despite the appealing narrative, the actual commercialization path remains unclear.

Over the past few years, AI monetization has been extremely narrow:

• Selling API parameters, charging per token
• Targeting niche groups like programmers with high willingness to pay

Personal agents take a completely different path. Their core moat is not model capability alone, but:

• Scale effects
• User experience
• Seamless penetration into daily workflows

In this high-concurrency, high-computing phase, profits will flow first to cloud sandboxes and hardware infrastructure. Big tech must continuously pay for computing power.

While Meta claims "most users free, heavy users pay subscription," specific pricing, ad-sharing models, and commission rates remain undisclosed.

Will the model rely on subscription fees to cover high CPU costs? Or will it extract commissions by taking over transaction gateways?

Until these commercial pathways are defined, the market's enthusiasm for gateway restructuring is essentially prepaying a premium for an uncertain commercial expectation.

04 Conclusion

Muse's explosive popularity handed hot money a convenient reason to buy. With oil prices falling and inflation easing, the broader market is in a window of risk appetite recovery, with capital eager for the next tech story.

Returning to the original question: This is not a valuation revaluation based on realized performance. It is an emotional prepayment and position covering timed to a favorable macro window.

What the market has bought is a set of unproven long-term assumptions. Since it is an assumption, patience is required for validation. No matter how impressive the download numbers, if users don't stay and cash flow doesn't materialize, it will ultimately be a fleeting illusion.