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Chinese startup Moonshot AI has unveiled a new model it says closes the gap with leading U.S. offerings and surpasses OpenAI and Anthropic's most capable systems on some benchmarks. Kimi K3 still trails Anthropic's Claude Fable 5 and OpenAI's GPT 5.6 Sol on overall performance, the company said on Friday, but consistently outperformed other tested models. The model beat Claude Opus 4.8 and GPT 5.5 — models that sit just behind Anthropic and OpenAI's leading-edge systems — on benchmarks including coding and general agents, according to Moonshot. It's China's largest AI model so far, with 2.8 trillion parameters, referring to the size of its neural network. "Despite persistent hardware/compute capacity constraints in China, K3 demonstrates that pre-training scaling, paired with architectural innovation, can still deliver step-change gains for flagship Chinese models," Bank of America analysts said in a note led by Alex Liu. The release comes as the race for AI supremacy between the U.S. and China intensifies. Chinese AI models are already gaining traction among Western companies as they close the performance gap with U.S. rivals and remain cheaper to use than the most advanced offerings from American labs. U.S. lawmakers are considering how to curb the growing adoption of Chinese AI models by homegrown companies.
Another DeepSeek moment?
Patrick Moorhead, the CEO and chief analyst at Moor Insights and Strategy, characterized the market's reaction to the new Kimi K3 model as "an over-reaction shockingly similar the DeepSeek panic," explaining in a post on X that despite the technology's advances, "We are far away from super-intelligence." Moorhead said in the post that large language models, or LLMs, like Kimi K3 will only "accelerate and grow the inference market faster than without," underscoring a general shift in the tech sector from merely focusing on the size and presumed capabilities of a model by itself to the overall application that the technology powers. Perplexity CEO Aravind Srinivas told CNBC last week that there's more focus from startups and developers to figure out the best methodologies for using AI models that can power their apps, instead of squarely focusing on one gigantic, underlying system. That's part of the reason why the freely available OpenClaw technology became so popular with developers earlier this year. The so-called harness lets coders more easily swap in and out various AI models that power digital assistants so they can take a series of actions without needing to rely on one single LLM by itself. "The model alone is no longer the product," Srinivas said at the time. "It is the harness, the orchestration system that puts the model inside a very capable harness and pairs the model with a lot of tools."
Moorhead attributed what he believes to be an overreaction to Kimi K3's release to politics, telling CNBC in an email that "There's a big debate in Washington DC about whether the U.S. should use Chinese open source models and if U.S. companies should enable the Chinese to use their models." "The latter is ironic as the Chinese seem to be doing fine with their models," Moorhead said. Lu Zhang, the founder and managing partner of the Fusion Fund, said that despite the widespread attention models like Kimi K3 can receive, most of the developers that use the technology are "from the startup ecosystem, less from the large corporate side." These coders will often swap one AI model out when there's a more powerful version available or at least one that's cheaper and more efficient to run in their respective apps, she explained. And while these AI models may seem extremely powerful at first glance, they are not "plug and play" and they require a lot of technological know-how from developers to actually make use of their underlying capabilities, Zhang said. Although general discourse involving the open-weight AI model space can often involve the broader "narrative of U.S.-China competition," Zhang said that there are several U.S. companies that are increasingly debuting open-weight AI models. Two of those are Thinking Machines and DeepReinforce, which is backed by Zhang's fund. She said it was only a matter of time that a more advanced open-weight AI model captured the zeitgeist, given how fast the overall space is moving. Similar to how the debut of DeepSeek's R1 AI model in 2025 generated attention for presumably being more cost-efficient relative to proprietary technologies, the current hoopla over Kimi K3 can be attributed to rising concerns about AI's overall cost and ability to generate returns on investment. Simon Koser, the chief product officer at the AI startup Tzafon, said that Kimi K3 is legitimately impressive in that it is performing well in areas like coding, and developers at AI labs could find it compelling. "Cost has become a huge thing for some of these labs," Koser said, underscoring how AI leaders like Anthropic and OpenAI may feel some pressure from cheaper AI models being available on the market. Still, there are many ways to use the technology, and not every AI model excels in every task despite what the initial benchmark tests may show. Certain AI models may react differently when put in production versus when they are tested, and there's no true jack-of-all-trades AI model that's superior to everything else on the market. "It's going to seem like a lot of people are changing," Koser said. "But in practice, I'm not sure if the shift is that huge."
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