Chinese artificial intelligence startup Moonshot AI has temporarily suspended new subscriptions to its flagship Kimi K3 model after demand overwhelmed its computing infrastructure, highlighting one of the industry’s biggest challenges as developers race to build ever more powerful AI systems.

The capacity crunch comes at a pivotal moment for the company, which is seeking up to $2 billion in fresh funding and preparing for a potential Hong Kong initial public offering (IPO) that could value the startup at around $30 billion.

According to sources cited by Reuters, Moonshot is restructuring its corporate organization by unwinding its offshore holding structure ahead of the planned listing, while holding discussions with investment banks including Goldman Sachs and China International Capital Corp (CICC) about a Hong Kong IPO.

Although preparations are underway, the listing timetable remains flexible, underpinning uncertain market conditions and the company’s rapidly evolving capital needs.

Moonshot said demand for Kimi K3, unveiled on Friday as what it describes as the world’s largest open-weight AI model with 2.8 trillion parameters, has significantly exceeded expectations. The company said user requests during the first 48 hours after launch approached the limits of its existing computing clusters, creating what it described as “unprecedented compute challenges.”

As a result, Moonshot immediately suspended new consumer subscriptions while preserving service quality for existing paying customers. Current subscribers will continue to receive uninterrupted access, while new memberships will be reopened gradually as additional computing capacity becomes available.

The company also announced that future subscription offerings will be divided into separate plans, including one specifically designed for coding workloads, allowing computing resources to be allocated more efficiently according to different user requirements.

In a post on X, Moonshot acknowledged the unexpectedly strong response.

“Kimi K3 has received far more love than we expected, and our GPUs are feeling it,” the company said.

The episode has revealed a common problem facing AI developers: success itself is becoming expensive.

AI Demand Is Shifting From Training to Inference

While companies initially focused their spending on training frontier AI models, the rapid growth in commercial usage has shifted attention toward inference computing—the processing power required every time users interact with AI systems.

Models such as Kimi K3 are particularly compute-intensive because they specialize in coding, reasoning, and AI agent workflows. Unlike simple chatbot interactions, these tasks often involve multiple rounds of model execution, longer context windows and repeated reasoning steps, significantly increasing GPU usage for each user session.

Although Kimi K3 is released as an open-weight model, allowing developers to download and modify it, analysts note that very few organizations can realistically operate a 2.8 trillion-parameter model independently because of the enormous hardware requirements.

Consequently, most users continue relying on cloud-hosted services, placing substantial pressure on providers’ data center infrastructure.

The computing bottleneck comes as Moonshot aggressively expands its capital base.

Founded in 2023 by Yang Zhilin, a former Carnegie Mellon University doctoral researcher, Moonshot has rapidly emerged as one of China’s leading AI startups. According to fundraising materials reviewed by Reuters, the company raised more than $2 billion in May from investors including Meituan, China Mobile and CPE, bringing its cumulative fundraising to more than $5.5 billion.

It has since begun seeking an additional $2 billion, with investor interest reportedly valuing the company at approximately $30 billion. The funding is seen as an indication of growing investor confidence that China’s leading AI companies are narrowing the performance gap with major U.S. developers while benefiting from lower operating costs and increasingly competitive open-weight models.

Moonshot’s experience also highlights the industry’s most significant operational challenge. Chinese AI companies have accelerated model development over the past year, with firms including Moonshot, DeepSeek, MiniMax, Z.ai and Alibaba releasing increasingly capable systems at a rapid pace.

However, access to computing infrastructure has emerged as the principal bottleneck.

U.S. export restrictions on advanced Nvidia AI processors have limited Chinese companies’ access to the world’s most powerful GPUs, forcing them to maximize available domestic computing resources while increasingly relying on Chinese alternatives such as Huawei’s Ascend AI chips.

Several leading startups, including DeepSeek, have reportedly sought additional funding specifically to expand computing capacity rather than model development alone. The shortage suggests that competitive advantage in AI is increasingly determined not only by algorithm quality but also by ownership of large-scale computing infrastructure.

IPO Reflects Broader AI Investment Boom

Moonshot’s planned Hong Kong listing would add to a growing pipeline of Chinese AI companies seeking public market capital.

Unlike earlier generations of Chinese technology listings centered on internet platforms and e-commerce, the new wave is driven primarily by demand for funding expensive AI infrastructure, including GPU clusters, networking equipment and data centers.

Investors have shown increasing willingness to finance these capital-intensive businesses as frontier AI models become central to software development, enterprise automation and digital services.

Moonshot’s rapid fundraising mirrors similar investment activity across the sector, where companies are raising billions of dollars not simply to build more advanced models but also to finance the computing capacity needed to serve rapidly expanding user bases.

However, the company’s infrastructure challenges come amid an increasingly competitive Chinese AI industry. Only days before Moonshot launched Kimi K3, rival developers including Z.ai and MiniMax introduced new large language models aimed at closing the remaining performance gap with leading U.S. systems.

Meanwhile, Alibaba, which is also a strategic investor in Moonshot, announced on Sunday that its Qwen3.8-Max-Preview, a 2.4 trillion-parameter model, had become available on its AI platforms ahead of a planned open-weight release.

The era of treating the “Magnificent Seven” as the dominant force driving U.S. equity markets has come to an end, according to Citi, which argues that investors should instead focus on a much broader group of growth companies benefiting from the artificial intelligence boom.

In a recent note to clients, the Wall Street bank said the once-dominant basket of mega-cap technology stocks is no longer an effective way to assess large-cap growth, as AI-driven earnings growth has spread well beyond the industry’s biggest names.

“The Mag 7 is dead as a construct for assessing large-cap growth dynamics, and it has been for some time,” Citi strategists wrote.

The bank’s view marks a notable shift in how Wall Street is assessing the AI trade, suggesting the market is moving into a second phase where gains are being driven by a wider range of companies rather than being concentrated in a handful of technology giants.

The Magnificent Seven, comprising Apple, Microsoft, Nvidia, Alphabet, Amazon, Meta Platforms and Tesla, dominated global equity markets after the generative AI boom began in late 2022. Their rapid earnings growth, dominant market positions and massive investments in artificial intelligence propelled the group to unprecedented valuations and helped lift the broader S&P 500 to successive record highs.

However, that leadership has weakened considerably this year.

The Roundhill Magnificent Seven ETF has gained just 1% in 2026, significantly underperforming the S&P 500, which has advanced about 9%.

The divergence indicates that investors have been increasingly cautious toward some of the market’s largest technology companies, amid concerns over lofty valuations, rising AI-related capital expenditure, slowing returns on investment, and uncertainty surrounding the long-term monetization of artificial intelligence.

Microsoft, the weakest performer among the seven this year, has fallen 17%, with recent losses driven largely by investor concerns over the company’s aggressive spending on AI infrastructure. Analysts say investors are increasingly scrutinizing whether the billions of dollars being invested in AI data centers, chips and cloud infrastructure will translate into sustainable earnings growth.

Citi Shifts Focus to A Broader “Growth Cluster”

Rather than expanding the Magnificent Seven into a larger technology index, Citi has shifted its attention to what it calls a “growth cluster.” The group, first introduced several years ago and recently refined by the bank, includes companies across six different industries that have contributed the most to S&P 500 earnings growth.

Collectively, these companies account for roughly half of the benchmark index’s total market capitalization.

According to Citi, the broader growth cluster has significantly outperformed both the Magnificent Seven and the overall market. The basket gained 25% during the second quarter and is up 12% for the year, compared with quarterly and year-to-date gains of 15% and 10%, respectively, for the S&P 500. It also outperformed Citi’s cyclical and defensive stock groupings, highlighting the continued strength of growth-oriented businesses even as market leadership broadens.

One of Citi’s central arguments is that artificial intelligence is no longer benefiting only the largest technology companies. Instead, earnings growth is increasingly being generated across semiconductor manufacturers, hardware suppliers, enterprise technology firms and industrial companies exposed to AI infrastructure spending.

The bank noted that if investors had instead owned an index consisting of the 25 companies contributing the most to S&P 500 earnings growth this year, they would have generated a 7% return, compared with just 2% from the Magnificent Seven.

That illustrates how leadership within the market has broadened beyond the familiar mega-cap technology names. Citi highlighted companies such as Intel, Applied Materials and Lam Research as examples of businesses making important contributions to corporate earnings growth, driven largely by strong demand for semiconductor manufacturing equipment and AI-related hardware.

However, the broader trend points to the evolution of the AI investment cycle. The first phase largely rewarded companies building foundational AI models and cloud infrastructure.

The next phase is benefiting suppliers of semiconductor equipment, networking hardware, enterprise software and specialized manufacturing technologies that support AI deployment across the economy.

Citi also pointed to consistently strong corporate earnings as a major reason for the growth cluster’s outperformance. Companies within the group have repeatedly exceeded analysts’ earnings expectations, allowing share prices to continue rising even as investors become more selective.

The bank estimates that the growth cluster now accounts for approximately 48% of the S&P 500’s expected earnings over the next 12 months. That concentration highlights how heavily overall market profits remain tied to companies benefiting directly or indirectly from AI-related investment.

Valuations Becoming More Attractive

Another reason Citi favors the broader growth cluster is valuation. After years of exceptional gains, several Magnificent Seven companies now trade at elevated earnings multiples, leading investors to seek cheaper opportunities elsewhere.

According to Citi, valuation metrics for the broader growth cluster are considerably more attractive. The bank said the group’s price-to-earnings-growth (PEG) ratio, which adjusts valuation relative to expected earnings growth, is currently near its lowest level in roughly 15 years.

That suggests many growth companies are offering stronger earnings prospects without commanding the premium valuations associated with the largest technology stocks.

Citi believes the market is still underestimating the long-term structural growth opportunity created by continued AI investment, particularly in semiconductors and hardware. The bank said forward growth expectations continue to be supported by sustained spending on AI infrastructure and ongoing supply constraints affecting parts of the semiconductor industry.

“As a result,” Citi said, “the stocks do not appear to be fully discounting a secular growth opportunity.”

The shift in market leadership comes amid increasing volatility across AI-related sectors.

Semiconductor and memory stocks, which had been among the strongest performers during the AI rally, have recently experienced sharp declines as investors rotated into other parts of the market. Over the past month, the iShares Semiconductor ETF has fallen about 18%, while the Roundhill Memory ETF has declined roughly 32%.

The pullback reflects profit-taking after an extended rally, as well as concerns over the pace of AI-related capital expenditure and whether demand can continue to justify current production expansion.

Nevertheless, Citi notes that artificial intelligence remains the dominant investment theme underpinning U.S. equity markets.

Rather than fading, the AI trade is becoming more diversified.

“We don’t think there is any one right way to perfectly describe how much of the S&P 500 reflects the AI trade,” the bank said.

“We believe our cluster approach to assessing the S&P 500 makes intuitive sense and gets us close.”

Using that framework, Citi estimates that roughly 55% of the S&P 500 is directly influenced by AI-related tailwinds or headwinds, while nearly half of the index’s expected earnings are generated by companies within its broader growth cluster.

The implication for investors is that the AI investment story is far from over. However, the next stage of the rally is likely to be driven by a broader ecosystem of companies rather than the handful of mega-cap technology stocks that defined the market’s first AI boom.

Paramount Skydance’s proposed acquisition of Warner Bros. Discovery has suffered a significant setback after a U.S. federal judge temporarily halted the transaction, marking the first major legal obstacle to a deal that would reshape the global entertainment industry.

U.S. District Judge Araceli Martínez-Olguín on Monday ordered a 14-day pause on the merger after hearing arguments from both sides last week, following a lawsuit filed by a coalition of 12 state attorneys general led by California Attorney General Rob Bonta.

The temporary injunction gives the states time to pursue a longer injunction that could further delay or potentially derail one of the biggest media consolidation efforts in recent years.

The proposed merger would combine two of Hollywood’s most influential studios and create an entertainment giant spanning film production, television networks and streaming services. It would bring together Paramount Pictures and Warner Bros. Pictures, while combining streaming platforms Paramount+ and HBO Max. The combined company would also control an extensive portfolio of television assets, including CBS, MTV, CNN and HBO.

The coalition of attorneys general argues that the transaction would substantially reduce competition across key segments of the entertainment industry. Their lawsuit contends that the merger would harm movie theaters, cable distributors, creative professionals and consumers by concentrating excessive market power in a single company.

According to the complaint, competition would be weakened in at least three major markets: wide-release theatrical film distribution, the distribution of top-grossing theatrical films, and licensing of programming to basic cable television providers.

“This is a critical first win in our case to ensure this megamerger never sees the light of day,” California Attorney General Rob Bonta said in a statement.

“History tells the tale of what happens when a few people have great power over markets that are central to Americans’ lives: fewer opportunities for more people, worse products and services for all people. With our lawsuit, we’re fighting for a free and fair market and a thriving film and television industry that serves creatives and audiences alike. We have a full tank of gas, the law on our side, and look forward to continuing to make our case.”

The case has added to the growing scrutiny of consolidation in the U.S. media and technology sectors as regulators challenge deals they believe could reduce competition, limit consumer choice and weaken bargaining power for content creators and distributors.

Paramount rejected the allegations, arguing that the merger reflects the realities of today’s highly competitive media landscape, where traditional entertainment companies face intense pressure from streaming leaders such as Netflix, Disney and Amazon.

“We are confident the evidence will demonstrate that the State AGs’ antitrust arguments are without merit as their alleged markets and claims of anticompetitive effects are without any basis in modern market realities,” a Paramount spokesperson said in a statement.

“This merger is lawful, pro-competitive, and will benefit consumers, creators, workers, and the entertainment industry. We will continue to vigorously defend the transaction and will look forward to the hearings on the substance of the State AGs’ action.”

The company says that combining their businesses would create a stronger competitor capable of investing more aggressively in premium content and competing with much larger global streaming platforms.

The legal challenge comes at a crucial time for Paramount. Chief Executive David Ellison said in May that the transaction remained on track to close by September, with the merger viewed as central to the company’s long-term strategy to strengthen its position in the increasingly competitive streaming market.

A prolonged court battle could disrupt that timeline, create uncertainty for investors and employees, and delay integration plans.

The merger has also attracted opposition from filmmakers, actors and other entertainment industry groups, who say that further consolidation would reduce the number of major buyers of creative content, potentially weakening negotiating power for producers, writers and performers while limiting opportunities for independent studios.

If ultimately approved, the combination would create one of the world’s largest entertainment companies, bringing together two of Hollywood’s oldest film studios, expanding content libraries across film and television, and strengthening the combined company’s ability to compete globally in streaming, sports broadcasting and premium television.

For now, however, the future of the transaction remains uncertain as the court considers whether the states have demonstrated sufficient antitrust concerns to justify extending the injunction beyond the initial 14-day period. A longer delay could complicate Paramount’s plans and prolong regulatory uncertainty surrounding one of the media industry’s most consequential proposed mergers.