On Thursday, Moonshot AI, a Beijing-based AI startup, unveiled the latest version of its Kimi large language model, which promises performance close to Anthropic’s Fable 5—perhaps the most powerful publicly available model today—at a fraction of the cost.
Kimi K3, the largest open-weight model ever released, performed “competitively” with Fable 5, and “substantially outperformed” Anthropic’s Opus 4.8, and OpenAI’s GPT 5.6 Sol, according to Moonshot. The company’s officially-released benchmarks consistently rank K3 among the top three AI models; one independent benchmark from Arena.AI even put K3 as the best model currently available, ahead of Anthropic.
Many observers, including Anthropic CEO Dario Amodei, didn’t expect a Chinese AI lab to release a model that could approach the U.S.’s best offerings for another six months. Tesla CEO Elon Musk, for example, suggested it might happen by the first quarter of next year. K3’s launch rapidly shrank that timeline and underscores just how quickly Chinese AI developers are closing the performance gap with their U.S. rivals.
“The AI ecosystem in China is probably much better than people thought,” says Paul Triolo, a partner at DGA-Albright Stonebridge Group.
Moonshot AI has priced K3 at $15 per million output tokens, the bits of information processed and generated by a large language model. That’s cheaper than Fable 5, which costs $50 for the same level of output.
Moonshot’s launch seemed to rattle investors who interpret the new model as undermining the conventional wisdom that U.S. firms can maintain their extended lead by simply outspending Chinese competitors on computing power.
A semiconductor selloff was already underway, but the K3 debut seemed to make things worse. Leading chipmaker Taiwan Semiconductor Manufacturing Company fell by 7% on Friday, despite reporting a 77% jump in quarterly operating profit. SoftBank—often seen as a proxy for OpenAI—fell by 9.0%. Z.ai, a Chinese AI startup that has released a competing model to Moonshot’s Kimi, plunged by almost 30% in Hong Kong trading.
Fear has spread into U.S. markets, with the Nasdaq 100 down by 1.0% as of 2:00pm Eastern time. Nvidia shares fell by 1.2%, briefly forfeiting the chipmaker’s lead as the world’s most valuable company to Apple. Meta shares plunged by over 2.4%.
Who’s who in China’s AI sector
China’s AI sector includes both established tech companies, like Alibaba and ByteDance; smaller startups like DeepSeek, MiniMax, and z.ai; and even dark horse entrants like phonemaker Xiaomi and food delivery platform Meituan.
Moonshot AI is one of the upstarts. Founded in 2023, its Chinese name comes from Pink Floyd’s album The Dark Side of the Moon, which is founder Yang Zhilin’s favorite album. The company is backed by Alibaba, Tencent, and Meituan, as well as HSG (formerly Sequoia China); it’s reportedly considering an IPO in Hong Kong.
This is Moonshot’s second time in the spotlight this year. Earlier Kimi models, notably K2.5 and K2.6, gained traction among Silicon Valley developers by offering strong coding performance at meaningfully lower cost than Anthropic’s Claude. In March, U.S. coding assistant maker Cursor acknowledged that its Composer 2 agent ran on top of Kimi 2.5.
It’s now taking its turn as China’s AI leader, a position that’s changed hands repeatedly this year.
In April, DeepSeek unveiled V4, its long-awaited update to last year’s V3 model. While V4 didn’t shock markets quite as much as its predecessor, it still offered frontier-level performance at rock-bottom prices—currently $0.87 for a million tokens of output—and its ability to be run on Huawei-made processors.
Fellow AI startup z.AI followed up in mid-June, with the release of its GLM-5.2 model. The Beijing-based startup announced the model just days after U.S. officials briefly disrupted access to Anthropic’s Fable and Mythos models for some users outside the United States and for foreign nationals. “Frontier intelligence should not belong to only a few people, nor be subject to withdrawal by a handful of rules at any moment,” the company wrote in a social media post announcing GLM‑5.2.
Even China’s consumer‑internet giants are getting into the frontier race. Meituan launched its own LongCat 2.0 model last month and revealed that it trained the system entirely on Chinese‑made semiconductors rather than U.S. chips.
“The idea that Meituan could train a 1.6 trillion-parameter model on domestic hardware would have been inconceivable in October 2022,” Triolo says, referring to the month when the U.S. launched sweeping export controls designed to slow China’s access to advanced AI chips.
Why are Chinese models cheaper?
Chinese AI has earned a global following by being systematically cheaper than the U.S. competition. DoorDash, for example, is pushing “lower-level work” to Moonshot’s Kimi model, leading to “better quality, cheaper cost,” according to chief technology officer Andy Fang.
Chinese systems routinely dominate the weekly leaderboards on OpenRouter, a popular marketplace that lets developers mix and match models from different providers. As of this week, all of the top five most-used models are from Chinese companies: Tencent, Xiaomi, DeepSeek, MiniMax, and z.ai.
Power costs in China are lower than in many parts of the U.S., in part because the country has made massive investments into power generation and transmission, making it easier to add data‑center capacity. New data centers in the U.S., however, often face political resistance due to perceived strain on grids and water use.
Chinese AI companies are also willing to sacrifice profit margins in a bid to capture market share and establish their models as a de facto standard.
Ironically, U.S. export controls—designed to hold China’s AI sector back—may also be a factor behind the low price of Chinese AI models. Without access to the most powerful AI processors, domestic labs were forced to squeeze more performance out of less capable hardware.
“Labs are so compute-constrained, capital-constrained, and talent-constrained that a lot of them are being cautious in how they use their resources,” says Grace Shao, an AI analyst and author of the AI Proem newsletter.
Most recent Chinese AI models are also now compatible with cheaper, locally-made processors. “For the money [a Chinese AI company would] spend on an Nvidia chip, they can buy ten local chips from Huawei or other local chipmakers,” says George Chen, a partner at the Asia Group.
Perhaps most importantly, Chinese companies have embraced the open-source movement, releasing their models for free. Almost all Chinese companies release their work under licenses that allow users to download models for free, run them on local hardware, and fine-tune them.
This allows third-party providers, including those in the U.S., to host Chinese models for free. The only costs that matter, in that case, are “GPUs and energy,” says Ameya Karnitkar, co-founder of Larridin, an AI measurement platform. “Anthropic adds the additional costs of their R&D, and their own inference costs.”
On July 17, at the World Artificial Intelligence Conference in Shanghai, China President Xi Jinping affirmed that the country will remain committed to releasing models on an open-source basis.
“We must seize this rare historic opportunity, encourage open source, openness, cooperation, and sharing, and comprehensively promote AI technological innovation, industrial development, and scenario-based applications,” Xi told conference attendees.
He also added a dig against Washington’s attempt to slap controls on the release of frontier models.
“We should jointly oppose the practice of overstretching the concept of national security in the field of AI or placing one country’s own security above the security of others.”
