Moonshot AI's Kimi K3 rivals US leaders, igniting fierce debate over open-weight models

China's Kimi K3 and the rise of open-weight AI models

Moonshot AI's Kimi K3 shows how opening a model to outsiders can turn other companies' computing power into a competitive advantage Just three days after the Chinese developer Moonshot AI unveiled Kimi K3 on July 17, it stopped accepting new subscriptions. Demand for the enormous artificial intelligence model had overwhelmed the company's available computing capacity. Yet Moonshot says it plans to release K3's full weights by July 27, which would allow other organizations to host and modify the model themselves. In a post on X, Dean W. Ball, OpenAI's head of strategic futures, argued that a world dominated by open-weight models could lead to "full AI communism" -- a future he described as "a dystopian hellscape." But giving away the weights of a top-tier AI model may actually make practical sense. For Moonshot, doing so could spread K3 far beyond the company's own computing infrastructure and help it compete with leading U.S. systems whose developers keep their weights private. Before reaching for dystopian prophecies, Ball acknowledged in the same post that Kimi K3, a 2.8-trillion-parameter system, appears to be a very good model. In benchmarks published by Moonshot, Kimi K3 generally lands ahead of OpenAI's GPT-5.5 and Anthropic's Claude Opus 4.8 but behind Claude Fable 5 and, on some tests, GPT-5.6 Sol. The company reports that it performs especially well on web searches and business workflows. These results place Kimi K3 among the strongest modern AI systems without showing that it has surpassed the leading American models. What most clearly sets K3 apart from GPT-5.6 Sol or Claude Fable 5 is Moonshot's plan to release its weights openly. On supporting science journalism If you're enjoying this article, consider supporting our award-winning journalism by subscribing. By purchasing a subscription you are helping to ensure the future of impactful stories about the discoveries and ideas shaping our world today. A large language model such as Kimi, GPT or Claude is, at bottom, an enormous collection of numbers. During training, the model ingests vast amounts of text and other data while an algorithm adjusts billions or trillions of numerical dials -- the weights -- until the system can predict and eventually generate humanlike content. Much of what the model has learned is encoded in those numbers. American AI labs generally keep the weights of their most capable models on private servers. A user can talk to GPT or Claude through an app but never possess the model itself. An open-weight release inverts this arrangement: The developer posts the trained weights publicly, allowing anyone with sufficient hardware to run the model privately or customize it. Chinese leaders have embraced that approach as part of a broader political message. At the 2026 World Artificial Intelligence Conference in Shanghai, Chinese president Xi Jinping called for "open source, openness, collaboration and sharing" to prevent "new historical injustice in AI." But that rhetoric blurs an important distinction. "Open weight is not the same as open source," says James Landay, a professor of computer science at Stanford University. There's been a lot of mixing up between the two." An open-source AI model should provide more than its weights, but also enough information and code for outsiders to study and modify the system -- although researchers and standards groups continue to debate how much of the training process must be disclosed. An open-weight release can leave the model's data and development history opaque. Landay says that uncertainty should make organizations cautious about adopting models whose provenance they cannot fully examine. "We might not know what's in there, we might not know if they phone home in some ways with our data," he warns. But such opacity does not erase the commercial logic of releasing the weights. "They still make money in a number of ways," says Kyle Chan, a fellow at the Brookings Institution who studies Chinese technology policy. Moonshot can continue selling access through its application-programming interface and subscription products even after other companies begin hosting K3. Moonshot is younger and less richly resourced than the largest U.S. frontier-model developers. Chan argues that releasing a strong model's weights gives such a company another way to compete: widespread adoption can expand its influence even when it lacks enough hardware to serve every user itself. U.S. export controls introduced in 2022 have restricted Chinese laboratories' access to advanced AI chips. "This constrained compute capacity for the Chinese AI labs," Chan says, "they talk about it all the time." The restrictions do not fully explain Chinese developers' embrace of open weights, but Chan says limited compute makes the strategy more attractive. Chan expects major hosting platforms such as Databricks to begin offering K3 after its weights are released. "By open-weighting it, you basically unlock all that extra compute capacity that other people have invested in and built up," he says, effectively turning outside providers' infrastructure into part of the model's distribution system. "It's like an amplifying effect." Meta helped popularize open-weight large language models when it released Llama in 2023. DeepSeek brought new attention to China's open-weight strategy with its R1 model in early 2025. OpenAI and Google now offer open-weight families of their own while reserving their most capable systems for controlled services. The U.S. startup Thinking Machines Labs joined the field on July 15 with its first model, Inkling. Chan believes the leading U.S. labs risk ceding ground if Chinese models become the systems that companies and developers around the world can most readily adopt. "I think it's a mistake to give up on open weight," he says. "The success of the Chinese models is showing its value." That doesn't imply China will necessarily win the AI race, Landay says. "New open models may come from those big players and not from Alibaba or the Kimi people," he says. "But if I could predict it, I'd be one of those rich guys driving an expensive car." Still, Landay expects competition from Chinese developers and smaller U.S. laboratories to put greater pressure on leading companies to release more capable open models. "I think the bigger lesson is that open ecosystems in the long run win," he says.

The US may find it hard to shrug off Moonshot's AI shockwaves

The latest Chinese models such as Kimi K3 look set to bring greater price competition More than a year after the DeepSeek shock, another "open" AI model from China has sent a severe tremor through Silicon Valley. This time, it may be harder for the US AI companies to shrug off the challenge. That has made a response from America all the more likely -- with unpredictable consequences for both the AI companies and their customers. The latest shockwaves were caused by last week's launch of Kimi K3, a model from Chinese start-up Moonshot that has come close to matching the most advanced competitors from the US frontier AI labs. The angst this has induced is reminiscent of the worries over DeepSeek's R1. Its low training costs appeared to threaten the far more expensive models being developed in the US. Wall Street came to terms with that threat, believing that US frontier models still had a meaningful lead, even if it had been cut to less than a year. But Kimi K3 -- along with other Chinese models like last month's GLM 5.2 and the Qwen 3.8 model that Alibaba announced at the weekend -- have all but erased the time advantage. Some US officials have been quick to accuse Moonshot of copying US rivals (using a technique called distillation) and getting around export controls on advanced US chips. There are signs, though, that innovation is playing an increasingly important part. Even a top executive at OpenAI conceded that Kimi K3's advances did not look like the result of copying, while its architectural improvements over earlier models have drawn admiration in the US. This looks like real competition, not just emulation. In economic terms, the competitive effects are not clear-cut. Open-weight models (a limited form of open-source software) are cheaper because the companies that develop them do not look to recover their training costs, and because they are run either on a customer's own systems or hosted by cloud-computing companies that compete on cost. Very large models like Kimi K3, though, are expensive to run. Also, the true cost to a user is not the price of a token (the basic unit of output, on which pricing is based), but the cost of completing a task. Some models use fewer tokens to do that, or generate fewer hallucinations (meaning less human labour is needed to validate their responses). That said, the latest spate of Chinese models looks set to bring greater price competition to the most advanced forms of AI. The question now is how US AI companies, as well as policymakers in Washington and Beijing, respond. The US frontier labs need to accelerate their shift from selling raw intelligence to packaging it into agents that can complete more valuable tasks. This worked with coding, but models like Kimi K3 are catching up fast on that front, forcing the labs to keep finding new uses. The stiffer competition also increases the urgency for frontier labs to get closer to their users, tapping customer data and business context to improve their relevance, while embedding their models into customers' workflows. The question for OpenAI and Anthropic is whether they can show real headway on these measures in time for their mammoth IPOs. The geopolitical ramifications are harder to predict. The Kimi K3 launch came just as President Xi Jinping was promoting open source AI as central to China's technology pitch to the world. Just days later, though, the FT reported that the country was considering export controls on some technologies -- including restricting access to the most advanced models' weights, the parameters which shape how they respond. This points to an emerging tension in the tech strategy of China Inc. Alongside an export-led drive geared to wide availability and low cost, there is a growing awareness of the need to defend homegrown technologies. It is not clear how that will play out. Washington, for its part, shows every sign of a knee-jerk response. Treasury secretary Scott Bessent signalled a possible crackdown on Chinese companies that use distillation -- though IP leakage from models that are publicly available would be hard to prevent. The US has other reasons to try to stem advanced Chinese AI, for instance the cyber risk the models might represent. Even if it succeeded in making its domestic market a protected zone for US frontier models, though, the result might be counter-productive in global terms. Companies in the rest of the world would still be able to access cheap Chinese models. And simply barring their use by US entities wouldn't solve the cyber threat.

China's Moonshot pauses Kimi subscriptions amid hot demand, IPO push

SHANGHAI/HONG KONG, July 20 (Reuters) - Chinese startup Moonshot AI has temporarily paused new subscriptions after demand for its newly launched Kimi K3 model strained capacity, a bottleneck that comes as the company seeks fresh funding and prepares for a potential Hong Kong listing. Moonshot is in the process of unwinding its current offshore structure ahead of a Hong Kong initial public offering, two sources with knowledge of the matter said. The company has engaged financial advisers including Goldman Sachs and China International Capital Corp to discuss the IPO plan, although the timetable remains fluid, said one of the sources and a third person with knowledge of the IPO plan, declining to be named as the information was confidential. CICC did not immediately respond to a request for comment. Goldman Sachs and Moonshot declined to comment. Founded in 2023 by Yang Zhilin, an AI researcher who pursued doctoral studies at Pittsburgh-based Carnegie ⁠Mellon University, Moonshot is one of China's most closely watched AI startups. It raised more than $2 billion in May from investors including Meituan, China Mobile and CPE, according to a fundraising teaser seen by Reuters, bringing the company's total historical fundraising to over $5.5 billion. It has since begun seeking up to $2 billion in fresh capital, with its valuation reaching $30 billion in June, the teaser showed. Strong demand for increasingly powerful models is boosting investor interest in China's leading AI startups, but it is also raising the need for costly computing infrastructure. Moonshot's competitors, including DeepSeek, have recently sought external capital to expand compute capacity as Chinese AI firms race to narrow the gap with U.S. rivals. Moonshot said on Sunday that since Kimi K3's release, it has drawn massive user interest, leading to "unprecedented compute challenges." Over the past 48 hours, user requests had sharply exceeded forecasts and were approaching the limits of existing clusters, the company said. Moonshot said it would pause new consumer subscriptions immediately and allocate available computing power to current paid users, who would be ⁠unaffected by the shortage. The company also said it would split future memberships into two plans, including one just for coding, a move aimed at matching compute resources more precisely with user demand. CAPACITY CRUNCH FOLLOWS KIMI K3 RELEASE The capacity crunch follows a strong reception for Kimi K3, which Moonshot unveiled on Friday as a 2.8 trillion-parameter model, making it the world's largest open-weight AI system, according to the company. "Kimi K3 has received far more love than we expected, and our GPUs are feeling it," Moonshot said on X, adding that new subscription spots ⁠would reopen in batches as capacity was added. Kimi K3's size and focus on coding and agent-style tasks make it more expensive to serve at scale, as such workflows typically require repeated model calls and heavy inference capacity. While open-weight models allow users to download and customise the underlying system, analysts say few users are likely to host a model of Kimi K3's scale ⁠themselves because of the hardware costs involved. Moonshot said Kimi K3 performed competitively with leading U.S. models in some technical tasks while independent evaluations have also pointed to strong performance. The launch comes as other Chinese AI firms such as Z.ai and MiniMax release more capable models at lower cost, challenging assumptions that China's model developers lag U.S. peers by ⁠months. Alibaba, an investor in Moonshot, said on Sunday Qwen3.8-Max-Preview, its 2.4-trillion-parameter model, had debuted on its AI platforms ahead of a planned open-weight release. U.S. export controls on advanced Nvidia chips, however, have made access to computing power a key constraint for these ambitious companies. Writing by Eduardo Baptista in Beijing; Reporting by Kane Wu in Hong Kong and Samuel Shen in Shanghai; additional reporting by Yantoultra Ngui in Singapore and Laurie Chen in Beijing; Editing by Sam Holmes Our Standards: The Thomson Reuters Trust Principles., opens new tab * Suggested Topics: * Disrupted * Capital Markets Kane Wu Thomson Reuters Kane Wu covers M&A, private equity, venture capital and investment banks in Asia. She tracks the region's most high-profile deals, fundraisings as well as investment trends amidst geopolitical, macroeconomic and regulatory changes. She was nominated for a SOPA Excellence in Business Reporting award for coverage of China regulatory crackdown in 2021. Prior to Reuters, she worked at the Wall Street Journal and also wrote about Asia's loan market for Thomson Reuters Basis Point. She is based in Hong Kong.

From Silicon Valley to DC, the tech world is suddenly obsessed with one concept in AI: Distillation

Leading tech companies published a letter on Friday urging policymakers to avoid "premature restrictions" on open-weight models that would "stifle competition or drive innovation overseas." Earlier this year, Google AI lead Jeff Dean, on a podcast, discussed a concept that, at the time, was hardly spoken about outside of wonky tech circles: distillation. In talking about the development of Google's AI models, Dean said that he and colleagues discovered artificial intelligence distillation techniques because Google was looking to improve performance on its systems without relying on one large image recognition model. "Through distillation, which is a key technique for making the smaller models more capable, you have to have the frontier model in order to then distill it into your smaller model," Dean said in February. Five months later, distillation has suddenly become a hot-button topic from Silicon Valley to Washington, D.C., as techies and lawmakers debate whether the practice is turning into a national security threat and enabling China to catch the U.S. in the high-stakes AI race. Concern bubbled up late last week after Chinese lab Moonshot AI released Kimi K3, and users quickly found it to be competitive with the best commercially available AI from Anthropic and OpenAI. Unlike the leading U.S. AI companies, which sell access to proprietary models, Moonshot and other Chinese labs are offering so-called open-weight models that allow users to download the technology, tweak it and run it wherever they want. Some government officials attribute Moonshot's ability to catch up so quickly to distillation, describing it as theft of American intellectual property, specifically by incorporating Anthropic's frontier Fable model. "We have information that Moonshot AI distilled Anthropic's Fable for the development of its K3 model," White House advisor Michael Kratsios posted on X on Wednesday. "To do this they developed a sophisticated internal platform to conduct large scale distillation against U.S. models, allowing them to quickly switch between multiple methods of access to avoid detection." At a high level, distillation refers to the use of answers from a chatbot or work product from an advanced AI model to train another model. The practice is controversial because, depending on how it's used, it can allow a model developer to create a competitive offering by simply using the output from companies that have invested many millions or billions of dollars developing the most sophisticated training technology. "It's almost like someone went to the lectures, read the textbook, and did all the hard work of doing the homework," said Pukar Hamal, founder of AI security firm SecurityPal. "Then some other student is like, 'Hey, I didn't do that. Can I just copy your work?'" Whether it was Kratsios' post or something else, the biggest tech heavyweights on the planet came together on Friday in what might be unprecedented fashion to make their position clear. After a series of social media posts throughout the week, tech giants Nvidia, Microsoft, Meta, Palantir joined with more than 20 other companies to release a letter urging policymakers to avoid "premature restrictions" on open-weight AI models that would "stifle competition or drive innovation overseas." "Distillation, or the practice of using one model's outputs to help train or improve another, is a widely used technique for model improvement, evolution, and validation," they wrote. The emergence of distillation presents a conundrum to U.S. policy makers, who have long been concerned about Chinese technology in terms of both IP theft and national security issues. Colin Shea-Blymyer, a research fellow at Georgetown's Center for Security and Emerging Technology, said the U.S. government is trying to figure out its position. The government could argue that Chinese and Russian companies "have used the outputs of hardworking American models to make themselves more performant, and so they have an unfair advantage there," Shea-Blymyer said. Box CEO Aaron Levie was one of the signatories of Friday's letter. Levie said in an interview that to stay competitive, U.S. companies need to be able to access the best technology, no matter where it's developed. "Generally the arc is going to be that the more innovation that there is, whether that's from the U.S. or China or otherwise, you should expect more AI progress, and generally it'll bend toward being even lower cost and more efficient over time," Levie said. Although much of the current discourse centers on Chinese open-weight AI models like Kimi K3, many companies have incorporated the distillation technique when creating their own models, said Shashi Bellamkonda, research director at Info-Tech Research Group. Nvidia, for instance, used distillation as part of the training process for its Llama Nemotron series of models, as detailed in an accompanying research paper. "It is a legitimate and a very valuable technique to train a smaller, cheaper model on outputs of a larger model, and is practiced all the time," Bellamkonda said. However, Anthropic has a different view, because the company sees how its models are being used and has a burgeoning business to protect. In February, the company said its Claude capabilities were being distilled on an "industrial scale" by China's DeepSeek, Moonshot, and MiniMax, which used about 24,000 fake accounts, generating 16 million exchanges. Anthropic, which is valued at close to $1 trillion and has aspirations of going public in the near future, said stopping illicit distillation was a matter of national security. "Anthropic and other US companies build systems that prevent state and non-state actors from using AI to, for example, develop bioweapons or carry out malicious cyber activities," the company said in its February post. And stopping it requires "rapid, coordinated action among industry players, policymakers, and the global AI community." OpenAI and Anthropic are banning distilling in their terms of service. Bellamkonda said they're essentially suggesting that using their larger models without authorization represents potential IP theft. But with AI costs skyrocketing, companies will do whatever it takes to drive efficiency. Hamal said he would have no problem using Chinese open-weight models like Kimi K3 at SecurityPal, which automates security assessments using AI. He says it could save them a lot of money. "We would make sure that there's no nefarious backdoors in the code," Hamal said. "But hosting it on our own infrastructure after we've done an assessment, why not?" One big problem for Anthropic and OpenAI as they try to make their case about IP theft is that both companies have relied on other sources of content to build their models, and have been sued for doing so. Max Pritt, an attorney for Boies Schiller Flexner who represents book authors in copyright litigation against AI firms, said the government is in the same boat. "The administration, at least publicly, has focused its efforts on the protection of technology companies' intellectual property, while remaining silent in large part about creators and individuals' intellectual property that was used without authorization," Pritt said. Choose CNBC as your preferred source on Google and never miss a moment from the most trusted name in business news.

Silicon Valley Splits Over Closing the Borders to Chinese A.I.

Mike Isaac and Kate Conger reported from San Francisco, Ana Swanson from Washington and Meaghan Tobin from New York. For years, a philosophical divide over how artificial intelligence software should be created has split Silicon Valley technologists. This week, that argument reached a boiling point. On one side are leading A.I. companies like Anthropic and OpenAI, which claim that A.I. models are too dangerous to be developed in the open and must be tightly controlled -- by businesses like themselves -- for safety. On the other is the rest of the tech industry, including giants like Microsoft and Nvidia, which contend that so-called open-source A.I. models must remain open for people to further develop technologies and build new businesses. Those camps have started publicly clashing. On Friday, Jensen Huang, Nvidia's chief executive, said in his first-ever post to X that "the world needs both frontier closed models and frontier open models." Nine minutes later, Satya Nadella, Microsoft's chief executive, posted that open-source software was "essential to a healthy A.I. ecosystem." Both signed a letter supporting open source, which was also signed by executives at Meta, Palantir and IBM. At the same time, OpenAI and Anthropic have lobbied regulators in Washington to restrict open-source A.I. models, five people close to the discussions said. The debate has drawn in Treasury Secretary Scott Bessent and Michael Kratsios, President Trump's science and technology adviser, who have weighed in on how American A.I. models are valuable intellectual property. The escalating fight stems from China's rapid progress in open-source A.I. models, which are freely available to use and build on. In recent weeks, two Chinese A.I. start-ups, Z.ai and Moonshot AI, have released models that rival those from Anthropic and other American labs. Anthropic and OpenAI have claimed that Chinese companies built the models by improperly harvesting data from their A.I. systems, which they said should not be allowed. But companies like Microsoft and Nvidia, which rely on open-source models to spur demand for their cloud computing services and chips, said that open-source software was important to advancing the technology with shared knowledge and that it would let more people examine its security. And for Silicon Valley start-up founders, constraining open-source software could cement the lead that OpenAI and Anthropic have in A.I., which critics argue could unfairly stifle other companies from building competing products. "You have two factions fighting over this issue," said Bill Gurley, a Silicon Valley venture capitalist who opposes restrictions on open-source software. "There's the people who want OpenAI and Anthropic to own everything, and then there's everybody else, including customers." Where this ends up has major implications not only for the U.S. tech industry but for the race between America and China to dominate the powerful technology. While China had a later start in developing cutting-edge A.I., it is catching up quickly in part because of its embrace of open source, which has helped Chinese labs improve by publicly sharing their systems and winning them customers around the world with lower prices. American A.I. companies, including Anthropic and OpenAI, have accused Chinese labs of "distilling" their systems by surreptitiously copying them, which has caught the attention of the Trump administration. On Wednesday, Mr. Bessent said the administration had considered imposing sanctions on Chinese companies that steal intellectual property from American firms. "Open source is not open season on American IP," he said, referring to intellectual property. That same day, Mr. Kratsios said that "large-scale, covert industrial distillation aimed at stealing proprietary U.S. technology and undermining American research is unacceptable." U.S. officials still appear to be debating their options, but seem more likely to approach regulating Chinese open-source models individually as a national security issue, rather than issuing some kind of blanket ban, four people with knowledge of the discussions said. Publicly, executives like Sam Altman, OpenAI's chief executive, have said they support open-source software even as OpenAI allies quietly lobby for restrictions. Others, like Google and Amazon, which have invested billions in companies such as Anthropic and OpenAI, are trying to stay out of the fray. (The New York Times has sued OpenAI and Microsoft, claiming copyright infringement of news articles. The two companies have denied the claims.) The open-versus-closed software debate has traveled around Silicon Valley since the tech industry's earliest days. Open-source proponents have argued that sharing information leads to improvements that make software safer and more reliable, while more rapidly spurring innovation. Opponents maintain that software is costly to develop, and that giving it away is just bad business. Today, much of the modern internet runs on open-source technologies, as do some of the most widely used computer systems, like Google's Android operating system. The Chinese government and tech industry have embraced the open-source path for A.I. Last year, a Chinese start-up, DeepSeek, unveiled an open-source A.I. system that rivaled those of American companies, shocking the industry. Other Chinese companies have followed. In a speech this month, Xi Jinping, China's leader, cast the country as a global champion of an open approach to the technology. China's advances have rattled executives at OpenAI and Anthropic, who are increasingly concerned that their longstanding head start is disappearing, two people familiar with the companies' internal deliberations said. "These American companies build these big, expensive models, and then the models take a detour to China, where they lose all their value," said Pedro Domingos, a professor emeritus of computer science and engineering at the University of Washington. "The American companies are justifiably outraged." To fight back, Anthropic and OpenAI are offering some cheaper A.I. models to businesses that may not need the "frontier" models that command higher prices. On Friday, Anthropic released Claude Opus 5, a model that he company described as "close to the frontier intelligence of Fable 5 at half the price." OpenAI is promoting similar lower-cost models. The real action is in Washington. Behind closed doors, executives from OpenAI and Anthropic, as well as investors in the companies, have cited concerns about the global economy, A.I. safety and national security as they try to persuade regulators to increase restrictions on Chinese open-source software, three people familiar with the discussions said. Sarah Heck, Anthropic's head of public policy, said in a social media post on Wednesday that "illicit, adversarial distillation is IP theft and industrial espionage that supports adversary military and intelligence capabilities." Anthropic executives claim that open-source models based on the company's software are too dangerous to let run amok. OpenAI executives are urging the Trump administration to enact policies requiring mandatory security evaluations of new A.I. models overseen by government agencies, the company said in a blog post last month, a move that could curtail open-source software development. OpenAI said it was "encouraged" by the work it was doing with the administration on the framework. Open-source proponents have spent the past week drumming up support to push back against OpenAI and Anthropic. On Wednesday, nearly 200 Silicon Valley start-ups, calling themselves the Little Tech Association, signed letters urging the Trump administration not to limit access to Chinese open-source models. Big Tech soon followed. On Friday morning, Elon Musk, Meta's Mark Zuckerberg and others lined up behind Mr. Huang and Mr. Nadella to support open source. "Jensen is right," Mr. Musk posted. "This has my full support." "Open source is a positive and important force," Mr. Zuckerberg wrote. One incident this week underscored the stakes of the divide. On Tuesday, OpenAI disclosed that a handful of its most advanced A.I. models broke containment during a test of their cybersecurity abilities, gained access to the internet and hacked the servers of an A.I. company called Hugging Face. OpenAI executives latched on to the moment as proof of how dangerous A.I. models can be even in a closed environment, emphasizing the need for regulation. Clement Delangue, the chief executive of Hugging Face, which is one of the most popular online libraries of open-source software, had a different point of view. To defend the company from OpenAI's hack, he turned to an open-source A.I. model created by China's Z.ai. In social media posts on Friday, Mr. Delangue made his position on the debate unmistakable. He said he planned to hold a march in San Francisco on Saturday to demonstrate support for open-source technology. "Open models for the win!" he wrote.

OpenAI quietly signs letter from Nvidia, Microsoft, and Meta warning about dangers of 'premature restrictions' on open-weight AI models -- as the White House accuses China of stealing from Anthropic

* Several AI companies in the US have published an open letter * The letter is campaigning for unrestricted open-weight AI * Meanwhile the US government accuses Moonshot AI of IP theft Any hopes AI tech reporters may have had about easing quietly into the weekend have been dashed by some of the biggest names in the business sharing an open letter in support of open-weight AI models -- while the White House has accused China of 'large scale' theft from US companies in building its open-weight AI. Nvidia CEO Jensen Huang got the ball rolling with his first-ever tweet, linking to a statement championing open-weight AI models, those models that can be downloaded, viewed, and edited by anyone. Models like this are essential for making AI "more accessible, adaptable, and widely available" the open letter says. It's co-signed by a slew of well-known tech and AI companies, including Meta, Microsoft, Perplexity, and IBM. While ChatGPT developer OpenAI -- which has had more of a closed-model focus, to date -- didn't appear on the original post from Huang, it has now also backed the sentiments. Essentially, these companies are campaigning for openness in AI to drive innovation and access, while also arguing against 'premature restrictions' by governments. It's no coincidence that the US government led by President Trump has recently tried to take a more prominent role in evaluating AI models and deciding when they should be released. It's also notable that Anthropic and Google are missing from the list of backers to this open letter. We don't have any official comment yet from these companies, so it's hard to judge the reasoning -- Google regularly releases open AI models, after all -- but it could be something to do with recent accusations aimed at Moonshot AI in China. Open and closed Part of the background to this open letter is that Chinese company Moonshot AI stands accused of distilling Claude's (closed) Fable 5 model in order to build its own (open) Kimi K3. In simple terms, distilling works by asking millions of questions of an AI model, and using the responses as training data. It's something Moonshot AI has denied, while hyping up the potential of the open-weighted, freely downloadable Kimi K3 AI model, which is being released on Monday -- another factor in this open letter coming out now. The US government is calling it IP theft, and has issued some heavy-handed responses. "We support open-source AI and the innovation it unlocks," US Treasury Secretary Scott Bessent posted on X. "But open source is not open season on American IP. When PRC firms conduct covert, industrial-scale distillation attacks that cross the line into IP theft, sanctions and Entity List designations will be on the table." What Nvidia, Meta, Microsoft, and the other open letter co-signers seem to be doing is trying to get ahead of any potential clampdown by the US government on open-weighted models. While everyone agrees that these AI models are beneficial, it's not clear what the next regulatory steps might be. However, the open letter is vague and general enough that you can read between the lines in a variety of different ways. It may be intended to allude to the Moonshot AI case, or it may not. What's clear is that we're coming to a crunch point for AI regulation and innovation across the globe, and everyone has a perspective. Follow TechRadar on Google News and add us as a preferred source to get our expert news, reviews, and opinion in your feeds.

NVIDIA CEO Jensen Huang joins X with post backing open-weight AI

Jensen Huang has joined X, and his first post was not about GeForce GPUs, driver updates, or Blackwell. Instead, the NVIDIA CEO used his debut to share a letter signed by NVIDIA and 24 other companies urging US policymakers not to restrict open-weight AI models. "AI will transform every industry, power every company, and be built by every country," Huang wrote. "Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty. The world needs both frontier closed models and frontier open models." The letter, titled Open Weights and American AI Leadership, argues that restricting open models would stifle competition, push innovation overseas, and concentrate the gains of AI in the hands of a small number of companies. It also warns that relying exclusively on closed models creates a single point of failure. "If everything just becomes one single model, one single point of attack, one single source of failure, I think the world is much, much more vulnerable," Huang said separately to Axios. OpenAI and Anthropic are notably absent from the list of signatories, with both companies warning about the security risks posed by Chinese open-weight models. Those concerns have also reached Washington, where Trump is reportedly considering new restrictions on Chinese AI models following the release of Moonshot AI's Kimi K3. The model recently ranked third on Artificial Analysis' Intelligence Index, behind only Anthropic's Claude Fable 5 and OpenAI's GPT-5.6 Sol. NVIDIA does not particularly care which model runs on its chips as long as something does. Widespread open-weight model adoption means more people running inference workloads, which means more demand for the hardware and data center infrastructure NVIDIA sells. Conversely, US export restrictions on NVIDIA's most advanced chips have already reduced its China business significantly. Huang has opposed those controls for years. Huang addressed the Chinese model question, saying, "open-source models that are excellent should be used." He dismissed the idea that running a downloaded Chinese model creates a security backdoor, pointing out that open weights can be inspected, modified, and run entirely offline. On whether China could displace American AI labs, he was blunt: "Zero possibility." For now, NVIDIA users have a new account to @ the next time a driver breaks something. Whether Huang answers is another question entirely.

The second Chinese AI shock rattles US as China narrows the race

China's Kimi K3 AI model has emerged, significantly narrowing the technological gap with American frontier systems. This development has prompted intense debate across Silicon Valley and Washington regarding China's AI capabilities. The model's performance, affordability, and open-weight release strategy are unsettling for American observers. Concerns are rising about cybersecurity and national security implications of these advanced Chinese systems. Eighteen months after DeepSeek forced the United States to rethink assumptions about China's AI capabilities, another Chinese model has landed with similar force. Kimi K3, developed by Beijing-based Moonshot AI, has rapidly become one of the most discussed technologies in the global AI industry. Its benchmark performance, open-weight release strategy and lower operating costs have triggered intense debate across Silicon Valley, Washington and the research community. For many observers, the concern is that China appears to be narrowing the gap with the American frontier much faster than expected. From DeepSeek to Kimi: A second wake-up call When DeepSeek stunned markets in early 2025, many American policymakers and technology executives treated it as a warning that Chinese AI firms were becoming more capable despite U.S. export controls. Yet there remained a widespread belief that China's best models still trailed the American frontier by several months. Kimi K3 has shaken that assumption. The model vaulted into the top tier of global AI systems almost immediately after release, outperforming leading American models on some coding benchmarks while competing closely on broader evaluations. More importantly, it is being offered at significantly lower cost and will be released as an open-weight model, allowing developers, companies and governments to run and customize it themselves. That combination of performance, affordability and openness is what has made Kimi K3 particularly unsettling for American observers. As Axios put it, the model has "reset the AI race overnight" by challenging the notion that the United States enjoys a comfortable technological lead. Why Kimi K3 matters beyond benchmarks The significance of Kimi K3 goes beyond leaderboard rankings. For years, America's AI advantage rested not only on having the strongest models but also on maintaining a meaningful gap over competitors. Many governments and enterprises were willing to pay premium prices for OpenAI or Anthropic products because they offered capabilities unavailable elsewhere. Kimi K3 challenges that business logic. Even if OpenAI and Anthropic retain an edge at the absolute frontier, a model that performs close to that frontier while costing less and allowing full customization may be attractive to many users around the world. Axios noted that Kimi's very existence places pressure on the pricing power and business models of leading American AI companies. This is precisely why Kimi has generated such strong reactions in both industry and policy circles. The question is no longer whether China can produce advanced AI models but whether Chinese firms can offer alternatives that large numbers of global users may actually prefer. Silicon Valley's response: Surprise mixed with respect Among developers and researchers, the reaction has largely been one of surprise and grudging admiration. The Washington Post reported that a recent wave of Chinese models, including Kimi K3, has led experts to question how large America's lead really is. Researchers interviewed by the Post described Chinese systems as rapidly closing the gap and becoming increasingly competitive in areas that were previously dominated by American firms. Many technology analysts have been particularly struck by the speed of China's progress. As recently as this spring, assessments cited by Axios suggested Chinese models lagged the U.S. frontier by many months. Kimi K3's arrival suggests that timeline may have compressed dramatically. The reaction has not been uniformly pessimistic, however. Many researchers point out that OpenAI and Anthropic still appear to possess the most powerful systems overall. Yet even those voices generally acknowledge that Kimi represents a significant narrowing of the gap rather than a routine incremental advance. The Kimi K3 alarm in Washington If Silicon Valley responded with surprise, Washington responded with concern. White House AI adviser David Sacks became one of the most prominent officials to publicly react to Kimi K3. According to Axios, Sacks described the model's performance as "concerning" and argued that it demonstrated the danger of burdening American AI firms with excessive regulation while Chinese competitors continue advancing. Sacks found Kimi K3 as evidence that the US could lose its technological advantage if policymakers slow domestic innovation. His argument fits into a broader debate within Washington about how to balance AI safety concerns with geopolitical competition. "This is concerning," Sacks wrote on X, saying that for the first time a Chinese model has taken the top spot on the Frontend Code Arena, an AI evaluation platform, and is "scoring at or near the frontier" on other benchmarks. He argued America is "tying itself in knots" with its policy reactions to AI, including bans on new data centers and the recent push for federal agencies to pre-approve model releases. "This is how you lose the AI race," he wrote. "The rest of the world won't play by our rules if we bog ourselves down." The Washington Post reported that the Trump administration is now grappling with a difficult dilemma. On one hand, officials want to preserve America's lead in AI. On the other, they are increasingly worried about the cybersecurity and national security implications of increasingly capable systems. The result has been growing tension between innovation and security objectives. The distillation controversy A major part of the American response has focused on how Chinese firms achieved such rapid progress. Leading U.S. AI companies, particularly Anthropic, have accused Chinese developers of engaging in large-scale "distillation," a process in which outputs from advanced models are used to train other systems. Many in Washington and the U.S. AI industry believe Chinese firms may be benefiting from capabilities originally developed by American companies. These concerns have moved beyond corporate complaints and into the realm of government scrutiny. According to the Washington Post, multiple parts of the U.S. government are examining Chinese AI development practices and evaluating whether American firms are competing on a level playing field. The issue has become particularly sensitive because it touches on intellectual property, export controls and national security simultaneously. Jensen Huang pushes back on Kimi K3 One of the most striking reactions has come from Nvidia CEO Jensen Huang. While many officials portray Kimi K3 as a strategic threat, Huang has argued that Washington is drawing the wrong lessons. In an interview with Axios, he said American companies should be allowed to use excellent Chinese open-source models and warned against efforts to ban or restrict them. Huang's argument is that cheaper and more accessible AI models expand the overall market, driving greater demand for computing infrastructure rather than reducing it. He also rejected the idea that open Chinese models necessarily create security risks, arguing that openness allows greater scrutiny and adaptation. His position places him in direct disagreement with some policymakers and frontier AI labs that see Chinese advances primarily through the lens of geopolitical competition. The open-weight challenge One reason Kimi K3 has generated disproportionate attention is its open-weight nature. Many of America's strongest AI systems remain closed and tightly controlled. By contrast, Moonshot plans to make Kimi available for download and modification. This means organizations can run it on their own infrastructure without depending on a commercial provider. For supporters, this approach promotes innovation and wider adoption. For critics, it creates concerns about the spread of advanced capabilities, including cyber capabilities. The debate highlights a broader divide within the American AI ecosystem. Some view openness as a strategic advantage. Others increasingly see it as a security risk in an era of intensifying U.S.-China competition. China is closing the AI race with America The most important lesson from Kimi K3 may have little to do with Moonshot AI itself. For years, discussions about the US-China AI race often focused on whether China could reach the frontier. That question now appears increasingly outdated. The emerging debate is about how quickly China can match frontier capabilities after they appear and whether American companies can maintain a sufficiently large lead to justify their enormous investments. AI competition has become part of a broader struggle over economic and technological leadership. The contest is increasingly about who provides the digital infrastructure underpinning the global economy. Kimi K3 does not necessarily mean China has surpassed the US. American firms still possess some of the most capable systems in existence. But it does suggest that the gap is smaller than many policymakers believed and shrinking faster than many expected. That is why Kimi K3 has generated such an outsized reaction. DeepSeek raised questions about China's trajectory. Kimi K3 has intensified them. For Washington, Silicon Valley and the broader research community, the model is less a technological surprise than a strategic warning that the AI race is entering a far more competitive phase.

Demis Hassabis Backs Jensen Huang's AI Vision, Says 'A Strong and Secure Open Ecosystem Is Important' for

Hassabis Supports Open AI Models On Saturday, Hassabis shared Huang's post on X, supporting Nvidia's position that open AI models play a critical role in advancing innovation, security and global access to AI. "A strong and secure open ecosystem is important for the world to benefit from AI," he wrote. He highlighted Google DeepMind's contributions to open science and AI development, including projects such as JAX, Transformers, AlphaFold and Gemma open models. Hassabis said Google's Gemma models have been downloaded more than 300 million times and emphasized that responsible standards should guide the deployment of both open and proprietary AI systems. Huang Calls For AI Model Balance Huang shared a letter signed by Nvidia outlining the importance of open models. "AI will transform every industry, power every company, and be built by every country," he wrote. He added that "open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty." The Nvidia CEO argued that the world should not choose between open and closed AI, saying, "The world needs both frontier closed models and frontier open models." Tech Leaders Back Open AI Models Nadella called open-weight models "essential to a healthy AI ecosystem," while Zuckerberg said open source could empower users and prevent centralization. Disclaimer: This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors. Photo courtesy: Thrive Studios ID / Shutterstock.com Market News and Data brought to you by Benzinga APIs To add Benzinga News as your preferred source on Google, click here.

MoonShot CEO Says "OpenAI Didn't Invent Anything New," As Sam Altman Signs The Letter Calling For Open-Weight AI Models After The Fact And Under Pressure

It is wholly ironic that OpenAI, a company presumably founded on the principle that AI should be openly accessible to everyone, had refused to sign a letter advocating for open-weight AI models, with Sam Altman only conveying his support after the fact and under immense public pressure. At the same time, the CEO of Moonshot, a company that just unveiled the Kimi K3 open-weight AI model, one that seriously endangers the moat that both OpenAI and Anthropic were meticulously building around their proprietary models, has just issued a scathing take-down of OpenAI, demolishing its star credentials within the ecosystem. Moonshot CEO trivializes OpenAI's achievements, just as Sam Altman concedes to the public pressure by finally supporting open-weight AI models As we detailed on Friday, the who's who of the AI world, including NVIDIA, Microsoft, Meta, Dell, Perplexity, Palantir, Mistral AI, and more, have now issued a letter, calling on the Trump administration to ensure that the open-weight AI model ecosystem continues to thrive. Even so, Google, OpenAI, and Anthropic - entities who stand to gain the most from the US government's evolving protectionist stance - were curiously absent from the list of signatories. Well, Google's Sundar Pichai has just conveyed his support for the letter, and so has OpenAI, finally! Of course, the New York Times recently reported that both OpenAI and Anthropic have "lobbied regulators in Washington to restrict open-source A.I. models," which only makes OpenAI's sudden volte-face all the more jarring. Of course, as we noted on Friday, an open-weight AI economy stands a better chance of furthering healthy competition while reducing data security- and cost-related barriers, all the while aligning with the ethos of American democracy. OpenAI and Anthropic should not be allowed to become the ultimate arbiters of a technology as revolutionary as AI. Meanwhile, the CEO of Moonshot - the company behind the highly capable Kimi K3 model that spurred allegations of model distillation and a concerted campaign in Washington to ban open-source AI models from China - has just issued a withering take-down of OpenAI, suggesting that the now-iconic company "didn't invent anything new" but "combined three things the world already had." Follow Wccftech on Google to get more of our news coverage in your feeds.

ETtech Explainer: Why Moonshot AI paused Kimi K3 subscriptions within days

Chinese AI startup Moonshot AI has stopped new subscriptions for its Kimi K3 model. This decision follows a sharp surge in user demand for the advanced AI. Additionally, Kimi K3 is attracting attention for its high-end coding performance as well as for offering this capability at a much lower cost than competitors. Following a sharp surge in user demand, Chinese AI startup Moonshot AI has temporarily stopped accepting new subscriptions for its latest AI model, Kimi K3, which it launched last week.Kimi K3 has been attracting attention for offering high-end coding performance at a much lower cost than leading frontier AI models such as Anthropic's Fable 5 and OpenAI's GPT models.Subscriptions on holdIn a post on microblogging platform X, the official Kimi AI

Elon Musk, Mark Zuckerberg, Satya Nadella Show 'Overwhelming Support' for Open-Weight AI Models as OpenAI

Satya Nadella Calls for Open-Weight AI Nadella championed open-weight AI models, describing them as "essential to a healthy AI ecosystem." In a post on X, Nadella wrote, "Together with others across our industry, we are outlining a path for open-weight models to strengthen American competitiveness and expand economic opportunity, while protecting national security." Mark Zuckerberg, Elon Musk Rally Behind Open Source Zuckerberg echoed Nadella's message, posting on X, "Open source is a positive and important force for both empowering people and preventing centralization. Proud to support this." Musk later shared Zuckerberg's post, writing, "Overwhelming support for open source." Tech Giants Urge US To Back Open-Weight AI On Friday, Nvidia, Meta and Microsoft joined 22 other organizations in signing a statement urging U.S. policymakers to support open-weight AI models. OpenAI and Anthropic have reportedly been advocating tighter restrictions on Chinese open-source AI models, arguing they could be exploited once released publicly. The debate intensified after Beijing-based Moonshot AI launched its open-weight Kimi K3 model on July 16, which reportedly approached frontier-level performance and rattled chip stocks. Nvidia CEO Jensen Huang also backed the initiative, writing in his first-ever X post that open models "strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty." Disclaimer: This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors. Image via Shutterstock Market News and Data brought to you by Benzinga APIs To add Benzinga News as your preferred source on Google, click here.

Mark Zuckerberg, Microsoft CEO just made major AI decision

Jensen Huang has been one of the most prominent voices in technology for years, but he had never once posted on X (the former Twitter). On July 24, he did. What he chose to say with his first-ever post on the platform says a lot about the fight now underway over who controls the future of AI. Huang backed a letter titled "Open Weights and American AI Leadership," signed by 25 organizations including Nvidia, Microsoft, and Meta, calling on U.S. policymakers to support open-weight AI models rather than restrict them. Satya Nadella and Mark Zuckerberg both added their own statements on X. Elon Musk amplified the message. And two of the most visible companies in frontier AI, OpenAI and Anthropic, were not on the list. What Zuckerberg, Nadella, Musk, and Huang actually said about open AI models Nadella offered a clear policy argument. "Together with others across our industry, we are outlining a path for open-weight models to strengthen American competitiveness and expand economic opportunity, while protecting national security," he posted on X. Zuckerberg was more direct. "Open source is a positive and important force for both empowering people and preventing centralization. Proud to support this," he posted on X. Musk reshared Zuckerberg's post and added three words: "Overwhelming support for open source." Huang's first X post made the same argument. Open models, he wrote, "strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty." For a CEO who has never used the platform publicly before, choosing this particular moment to start says something about how seriously the industry is treating this debate. To understand why this fight matters, it helps to know what open-weight actually means. When a company releases a model as open-weight, it publishes the underlying numerical parameters: the billions of values that define how the model thinks and responds. Anyone can download those parameters, run the model on their own hardware, and modify it for specific tasks without paying API fees or asking permission. A business can deploy the model inside its own data center and keep its data off third-party servers entirely. A foreign government can take that model and run it without depending on any American company at all. That last part is where the geopolitical argument gets interesting, and where the two sides in this debate start talking past each other. Why OpenAI and Anthropic staying off the letter is the real story OpenAI and Anthropic weren't just absent. Both companies have reportedly been pushing U.S. policymakers in the opposite direction, advocating for tighter restrictions on Chinese open-source AI and arguing those models are easier to misuse once released publicly. The commercial interest behind that position is pretty clear. OpenAI and Anthropic charge for API access to models they control. Developers who can run equally capable models on their own infrastructure don't need to pay those fees. The open-weight push doesn't just put these two companies on the wrong side of a policy letter. It threatens a core part of how they make money. Critics of the letter are quick to point this out. They describe the industry push as lobbying dressed up as public interest. The argument that open models are harder to control once widely released is a legitimate one, and it's the issue OpenAI and Anthropic are raising with policymakers. What China's Kimi K3 launch has to do with the timing There's a specific reason the letter came when it did. On July 16, Beijing-based Moonshot AI put out an open-weight model called Kimi K3. It reportedly hit near-frontier performance levels. Chip stocks slid on the news. The release made something concrete that had been theoretical for months: Chinese labs can now build open-weight models that are genuinely competitive with what U.S. labs produce, and release them publicly for anyone to download. White House adviser Michael Kratsios accused Moonshot of using distillation to copy a U.S. model in building Kimi K3, adding another layer of tension to the debate, Fortune reported. For the tech leaders backing the letter, that development strengthens their case rather than weakening it. Their argument is that if China can produce and globally distribute competitive open-weight systems, the U.S. response should be to accelerate its own open ecosystem, not restrict it. Locking down open models in the U.S. would slow American innovation while doing nothing to stop Chinese models from spreading. Why the policy fight over open AI models is just getting started The policy stakes are real. Policymakers are currently weighing whether to restrict how openly AI models can be released, who can train on large amounts of compute, and how much access foreign entities should have to frontier systems. The letter from Zuckerberg, Nadella, and 23 other organizations is a direct attempt to influence those decisions before they become law. It argues that regulators should target specific harms and misuse cases rather than restricting the model format itself. The tech leaders signing it are betting that an open-weight ecosystem ultimately serves American interests better than a controlled one does. The ones who didn't sign are making the opposite bet. That divide is now public, and it will play out in committee rooms and policy briefings over the months ahead. Jensen Huang waited a long time to make his first X post. The fact that he used it on this issue is the clearest signal of how seriously the biggest names in the industry are taking this fight. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published July 26, 2026 at 5:03 AM.

Another 'DeepSeek moment'? What China's Kimi K3 means for the global AI industry - The Korea Times

Visitors at the booth for Moonshot's Kimi K3 during World AI Conference in Shanghai, July 17. AP-Yonhap The launch of Moonshot AI's Kimi K3 has revived an intense debate that has raged in Silicon Valley ever since DeepSeek's shock breakthrough last year: whether China can overcome its limited access to advanced chips to match the performance of the United States' frontier artificial intelligence models. Trillions of U.S. dollars might rest on the answer, as some see Chinese developers' success in increasing performance through architectural innovation as weakening the rationale for America's vast spending on AI infrastructure. The arrival of K3 has sent shock waves across the global AI industry. The 2.8-trillion-parameter open-weight model performed close to the latest frontier systems from OpenAI and Anthropic, fuelling concerns in Silicon Valley that China had closed its model-development gap with the U.S. to weeks rather than months. For some analysts, the launch is about more than a shift in the benchmark contest between U.S. and Chinese models. It offers a test of how China's advances in AI software could affect an industry built around US dominance in frontier models - and the computing hardware that powers them. "For much of the past three years, the global artificial intelligence story has been framed as an American one. OpenAI, Google and Anthropic have dominated headlines, while investors have poured money into the companies supplying the chips, memory and data centres needed to power the AI boom," said Sunil Tirumalai, head of emerging markets and Asia equity strategy at UBS, in a research note. "But a new question is beginning to emerge: what happens if Chinese AI models become much better - and much cheaper?" Several investment banks have described K3 as evidence that Chinese laboratories are moving beyond their earlier reputation for producing cheaper but less capable alternatives to Silicon Valley's top systems. Morgan Stanley said K3 represented an "all-round catch-up" in model scale, performance and pricing. Goldman Sachs described China's progression as moving from the cost efficiency demonstrated by DeepSeek to stronger intelligence and, with K3, a greater ability to charge for frontier-level performance. Bernstein said the model showed that China's leading laboratories could continue to keep pace with the U.S. frontier. Meanwhile, Chinese AI models are increasingly finding users outside China. Their appeal is not that they are the smartest models in the world. Rather, they are often "good enough" for many everyday tasks while costing a fraction of leading U.S. alternatives, Tirumalai said. But the emergence of cheaper, more efficient models from China does not necessarily mean that demand for underlying hardware such as semiconductors and data centres will fall. As some analysts have pointed out, when technologies become cheaper, people often use them more, not less. Moreover, there is evidence to suggest that K3 does not offer the dramatic cost reductions that some assume. Nomura, citing benchmark provider Artificial Analysis, estimated K3's average cost at about $0.94 per task, close to OpenAI's GPT-5.6 Sol. It is also worth looking back to what happened following the "DeepSeek moment" in January 2025. After the Chinese start-up's R1 model shocked global markets by matching top-tier U.S. systems at a fraction of the cost, there were widespread fears that Silicon Valley might have massively overinvested in AI compute. But after the shock died down, the world's technology ecosystem doubled down with huge capital expenditure on AI hardware, underscoring the idea that cost-effective models do not necessarily reduce compute demand. Washington is also seeking to reinforce America's existing advantage in computing resources. U.S. Treasury Secretary Scott Bessent said in an interview released this month that the U.S. could soon account for 80 per cent of the world's computing power, although he did not explain the methodology or provide a timetable. Tirumalai said total infrastructure demand depended on the computing required for each AI task multiplied by the number of tasks performed. Efficiency should reduce the first figure, but cheaper and more capable models could cause the second to rise more quickly as adoption expands. He compared the process with mobile communications. Successive generations of networks sharply reduced the cost of transmitting data, but overall consumption surged as video streaming, gaming and social media created new uses. "The rise of Chinese AI should not be viewed simply as a threat to today's winners," he said. "It may instead reshape where value is created and who captures it." Lei Meng, China equity strategist at UBS, said technology and AI would remain the main investment themes in 2026, with sectors linked to AI capital expenditure benefiting from spillover beyond narrowly defined AI spending. The more immediate pressure from K3 may therefore fall on the margins of model providers rather than on demand for computing infrastructure. Technology investor Gavin Baker argued that an industry dominated by only a few frontier laboratories would allow those companies to preserve high inference margins and gradually expand into infrastructure and software. But greater competition from Chinese and other open-weight models could make it harder for OpenAI and Anthropic to capture such a large share of AI spending. That could leave more spending for chipmakers, cloud providers, data-centre operators and application developers. Models developed in China would still require processors, memory and electricity wherever overseas users choose to deploy them, according to Baker. Moonshot's own roll-out offers an early test of that argument. Despite claiming a sharp improvement in development efficiency, the company is still racing to bring more graphics processing units online after demand for K3 overwhelmed its existing capacity. Read the article at SCMP.

Kimi K3: China's Moonshot AI pauses new Kimi K3 subscriptions amid surge in demand

In a social media post, Kimi AI stated the surge in demand over the last 48 hours has pushed the company's current capacity close to its limits. Hence, to ensure a stable experience for existing subscribers, new subscriptions have been temporarily paused. China's Moonshot AI has temporarily paused new subscriptions for its latest AI model Kimi K3 amid a sharp surge in demand, as per a statement by the company. In a social media post, Kimi AI stated the surge in demand over the last 48 hours has pushed the company's current capacity close to its limits. Hence, to ensure a stable experience for existing subscribers, new subscriptions have been temporarily paused. "Over the past 48 hours, demand has pushed close to the limits of our current capacity. To protect the experience of existing subscribers, we're temporarily pausing new subscriptions and prioritising compute for current members," it said. The company further noted, while compute resources are being prioritised for current members, "Existing subscribers will not be affected." Apart from this, the company is adding further capacity and will reopen new subscription spots in batches. "We're adding capacity as fast as we can and will reopen new subscription spots in batches," it said. Furthermore, the company will also introduce two more focused membership plans to enable more precise allocation of computing resources and help maintain a stable user experience. "Going forward, we'll also split membership into two more focused plans: Kimi Membership for Kimi Web, App, and Work; and Kimi Code Membership for coding workflows. This will help us match compute more precisely and keep the experience stable," it said. Developed by the Chinese startup Moonshot AI, Kimi K3 is a 2.8 trillion-parameter model with a 1-million-token context window. "It is the world's first open 3T-class model, designed for frontier intelligence across long-horizon coding, knowledge work, and reasoning," the company said in its blog. "Kimi K3 is available today on Kimi.com, Kimi Work, Kimi Code, and the Kimi API. At launch, Kimi K3 will use max thinking effort by default, with low- and high-effort modes to be introduced in subsequent updates," the company added. The full model weights will come out by July 27, 2026. The startup claimed that its model delivered frontier-level performance across its evaluation suite, although it still lagged behind Claude Fable 5 and GPT 5.6 SoI. (ANI)

Nvidia, Micron just got hit by Kimi K3 AI model from Beijing

Every market boom eventually runs into the same problem, and it rarely shows up where investors expect it. You ride a simple story - in this case, artificial intelligence needs endless chips and data centers - straight up the chart until the numbers stop feeling real. Then something jolts the narrative, not by breaking the old leaders, but by proving they aren't alone anymore. Right now, that jolt is coming from Beijing. Chinese startup Moonshot AI just introduced Kimi K3, an open‑weight artificial intelligence model built with roughly two point eight trillion parameters, a scale that rivals the largest systems in the world. Independent benchmarks cited by outlets such as the BBC say Kimi K3 performs in the same neighborhood as top models from OpenAI and Anthropic on many reasoning and coding tasks. Kimi K3 is not about stealing Nvidia's customers overnight. Still, my take is that it attacks the assumption that U.S. companies will always enjoy a comfortable technological lead, and that is exactly where the market decided to hit the brakes. Chip investors just got a wake‑up call Nvidia's stock, along with Micron Technology and other chipmakers, slid as traders digested the idea that a Chinese lab could make top‑tier artificial intelligence models cheaper and more accessible, The Wall Street Journal reported. The PHLX Semiconductor Index fell about 10% in the week of Kimi K3's launch, its steepest weekly drop since April 2025, as investors dumped AI‑linked names, The Journal reported. More Artificial Intelligence: Tech stocks broadly sold off, with the Nasdaq down roughly one point four percent, but chipmakers took the brunt because their valuations are built directly on artificial intelligence demand. David Sacks and Bill Ackman have been warning that China's new model narrows America's lead in artificial intelligence and heightens policy and national‑security risks around data centers and cloud infrastructure, according to Benzinga. Their argument is simple, and it matters. If you own these stocks or work in the sector, cheaper high‑end models from China could force corporations and governments to rethink how much they spend on Western chips and cloud capacity. VCG / Getty Images What is the Kimi K3 AI model? Kimi K3 is Moonshot AI's latest flagship model, built as an open‑weight system that developers can download, inspect, and modify, unlike the closed models most U.S. users rely on. The model clocks in at around 2.8 trillion parameters, making it the largest open system yet disclosed from China and placing it firmly in the same size class as elite Western models, according to the BBC. Artificial Analysis and other benchmarking firms have found that Kimi K3 competes closely with leading reasoning models, ranking near the top on tasks like web interface engineering and complex coding. On paper, this does two things investors care about. First, it proves that China's labs can match or nearly match state‑of‑the‑art performance in core commercial tasks such as software development and data analysis. Second, by making such a system open and, in some configurations, cheaper than Western closed alternatives, it threatens the idea that only Silicon Valley giants can deliver cutting‑edge artificial intelligence at scale. At‑a‑glance numbers behind the Kimi K3 shock * Kimi K3's parameter count is about 2.8 trillion, according to BBC and Inc. * Weekly drop in PHLX Semiconductor Index, roughly 10%, The Wall Street Journal reported. * Nasdaq declined on the main sell-off day, around 1.4%, The New York Times confirmed. * Nvidia and other chipmakers' intraday moves were between 2% and 4% percent down. When I compare those numbers against how fast Nvidia and its peers ran up this year, I believe that this is less a crash and more a sentiment reset around how durable the AI spending story really is. Why Kimi K3 matters for your wallet If you own Nvidia or Micron, you are basically betting that artificial intelligence workloads keep growing faster than anyone can build cheap alternatives. Kimi K3 does not demolish that thesis, but it introduces real competition in what used to be a one‑way narrative. TheStreet has covered how investors hope strong Nvidia earnings can give the broader rally more life, and how analysts are still raising price targets ahead of big quarters, but days like this show that the path will not be smooth. Cheaper or open models from China could push some companies to experiment with lower‑cost infrastructure or shift workloads, which would chip away at the premium multiples that data‑center suppliers enjoy. For workers, especially in tech and cloud‑related roles, this is a reminder that if artificial intelligence becomes more globally commoditized, the pricing power and hiring power concentrated in a few U.S. giants could spread out, or in some areas, shrink. For your kid growing up into this market, the story might not be about one or two American companies owning the future, but about whether they can stay ahead of a crowded field where China, and other countries, release powerful tools for anyone to build on. How to think about Nvidia and Micron now Short‑term, this kind of shock tends to pass once investors see hard earnings data. Part of the volatility in chip stocks has been driven by traders locking in profits ahead of major quarterly reports from Nvidia and other megacap technology names, The Journal noted. If those numbers show that demand for U.S. chips and cloud capacity is still growing, the Kimi K3 headlines may fade into the background, at least until the next competitive threat emerges. Long‑term, though, you should be asking different questions about your exposure to AI‑linked names. Do you own them because you believe they can stay ahead of global competition, including open systems from Beijing, or because you assume their lead is guaranteed by politics and hype? If it is the latter, this week is a warning to rethink that assumption. I would treat this sell-off as an opportunity to revisit whether your portfolio is overly concentrated in a single story (i.e., artificial intelligence needs endless Western chips). It's clear that AI technology itself is becoming cheaper, more open, and more evenly distributed around the world. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published July 21, 2026 at 2:47 PM.

This Chinese AI Model Became So Popular It Stopped Taking New Users -- and Analysts Say Nvidia, Micron Coul

Two days after its launch on July 17, Moonshot AI temporarily stopped new sign-ups for its Kimi K3 model due to high demand and compute constraints. Anni Sen, managing partner of BluBird Capital, told MarketWatch that the surge in demand for Kimi K3 indicates a potential long-term increase in chip demand. She stated that this development is "a positive tailwind for the memory trade." While Kimi K3 is efficient to run, the model's need to hold 2.8 trillion parameters in active memory could make it challenging for enterprises to operate on their servers, according to Sen. This could lead to an increase in AI workloads and further boost demand for chips. Wedbush analyst Matt Bryson noted that if Chinese AI models continue to gain traction, it would be "arguably good for memory vendors," as demand for high-performance memory is expected to rise. Over the past 5 days, SK Hynix stock declined 10.05%, while Micron stock dropped 12.29% on the NASDAQ Meanwhile, SK Hynix's Chairman Chey Tae-won has argued for expanding memory supply rather than maximizing profits from the current shortage. He expects overall memory demand to rise by more than 50% to 60% next year, with AI-specific demand potentially climbing by 60% to 100%. Disclaimer: This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors. Image via Shutterstock Market News and Data brought to you by Benzinga APIs To add Benzinga News as your preferred source on Google, click here.

Kimi K3 Raises Fresh US Concerns Over China's Fast-Growing AI Capabilities

China's Moonshot AI has drawn global attention after releasing Kimi K3, an open-weight artificial intelligence model that competes with leading US systems on several tests. The model is available to developers at no cost and can run on private servers. Demand rose quickly after its launch. Moonshot stopped accepting new subscriptions within two days after computing demand exceeded available capacity. Its early growth has added pressure to the technology race between China and the United States. has also triggered fresh claims from US officials about access to restricted NVIDIA chips and the possible use of American model outputs during training. Moonshot has denied the claims.

China's Moonshot AI pauses subscriptions for powerful Kimi K3 model due to surging demand

Chinese AI firm Moonshot has paused new subscriptions for its powerful new Kimi K3 model due to high demand - days after it was released with capabilities rivaling those of OpenAI and Anthropic. The Beijing-based Moonshot said Sunday it was grappling with "unprecedented compute challenges" and would temporarily focus on ensuring it could serve its existing paid users. The large-language model was trained on 2.8 trillion parameters, making it the largest open-source model ever released. "Kimi K3 has received far more love than we expected, and our GPUs are feeling it," Moonshot wrote in an X post. "Over the past 48 hours, demand has pushed close to the limits of our current capacity." Moonshot was founded in 2023 by AI researcher Yang Zhilin, who once studied at Carnegie Mellon University in Pittsburgh. His firm is one of several Chinese AI startups that have gained steam in recent months while releasing powerful open-source models that are available for a fraction of the cost of Anthropic and OpenAI offerings. Benchmark tests showed Kimi K3 outperforming Anthropic's Opus 4.8 model and OpenAI's ChatGPT 5.5 on most coding tasks, though it is still less powerful that Anthropic's cutting-edge Fable model. Meanwhile, Moonshot has begun talks with Goldman Sachs and other firms about a potential initial public offering in Hong Kong, Reuters reported, citing sources with knowledge of the matter. The company, which has raised more than $5.5 billion from investors to date, has seeking an injection of $2 billion in new capital, the outlet reported. Moonshot's valuation was $30 billion as of June. Some US officials are fretting that China is catching up to American firms in AI development despite tough export controls that have limited the country's access to the best computer chips offered by Nvidia. As The Post reported, Anthropic and OpenAI have each accused Chinese rivals in recent months of using unauthorized distillation - in which a more advanced AI model is used to train a new one - to rip off their technology. Last February, Anthropic directly accused Moonshot and two other Chinese firms, DeepSeek and Minimax, of distilling its models. So far, Anthropic has not said whether it suspects distillation was used to help build Kimi K3.