The U.S. government’s decision to stop Anthropic from offering its Mythos and Fable 5 models to non-U.S. nationals may end up providing a big boost to the adoption of open-source models, including those from Chinese AI labs like DeepSeek and Moonshot AI.
Users can download open-source models and run them on their own computers or cloud networks, effectively sidestepping the ability of both AI developers and governments to control access. These models can also be more easily fine-tuned by developers to tailor them for specific needs.
Chinese labs are already claiming a public relations win from the Anthropic controversy.
Shares in Knowledge Atlas, a Chinese AI lab better known as z.ai, surged by over 30% in Hong Kong trading on Monday after it released the latest version of its open-source model, GLM-5.2. (Knowledge Atlas’s shares are up more than 800% since they debuted in January)
“At a time when some frontier models can suddenly become unavailable, we choose to believe in a different path,” Knowledge Atlas posted on social media, according to the South China Morning Post. In a clear reference to the Anthropic news, the company added that “frontier intelligence should not belong to only a few people, nor be subject to withdrawal by a handful of rules at any moment.”
Demand for Chinese models has already overtaken that for U.S. models on OpenRouter, a popular platform for accessing different AI models. Last week, the top four most-used models came from Chinese companies: DeepSeek, MiniMax, Tencent and Xiaomi. The Chinese open source models have proved popular not just within China but also in many other developing countries around the globe, where they are seen as a good trade off between price and performance.
The U.S.’s ban on Fable and Mythos may also end up vindicating China’s broader move towards tech self-sufficiency, which picked up in 2022 after the Biden Administration placed controls on the sale of advanced chips and chipmaking equipment. “It’s a great move for China,” says Neil Shah, vice president of research at Counterpoint Research. “Obviously they’re not on the cutting edge because of the export controls, but they have their own silicon and their own software.”
Why go open-source?
On Friday, Anthropic revealed that the U.S. Department of Commerce had ordered it to stop providing access to its frontier models to anyone outside of the U.S. The way U.S. export rules are interpreted also means the company cannot offer the models to any “foreign national” inside the U.S., including its own employees. In response to the government order, the company decided to suspend access to these models to all users.
Anthropic had previously argued that its Mythos model was too powerful to be released to the public without safeguards, and had embarked on an early-access program, titled Project Glasswing, for key institutions to use the model to uncover security vulnerabilities. Institutions in about 15 countries, including U.S. allies like Japan and South Korea, eventually got access to Mythos through Project Glasswing.
But the U.S.’s move against Anthropic raises the possibility that frontier models from other labs, like OpenAI or Google, might also get hit by export controls. In that event, non-U.S. organizations may be completely locked out from accessing the best U.S.-developed models.
Open-source models could be an alternative, particularly for governments hoping to invest in sovereign AI, domestically-developed and -controlled AI models and infrastructure. The U.S.’s export controls on Anthropic only highlights the danger governments have from being locked in to one country’s AI models.
“It is the first time that a government has ordered a model developer to restrict access to a particular model based on nationality,” says Paul Triolo, a partner at DGA-Albright Stonebridge Group. “Companies and governments will start reconsidering how they are approaching application development based on a particular model, and for governments, which companies they will want to partner with for sovereign AI deployments.”
“Until there is further clarity about what criteria the U.S. government will use in assessing and approving frontier models, companies and governments will definitely be exploring options such as non-U.S. origin models,” such as those from Mistral, Cohere, and “capable Chinese open-source models,” he adds.
The Anthropic order will “push scale for Chinese open-source models,” Shah says. “But we’ll also see lots of ambitious and self-sufficient economies, like in the Middle East, who will try to build their own indigenous software models.”
Asian governments in particular have made a public push for “sovereign AI.” South Korea, for example, launched a national state-backed competition to develop Korean-language AI models.
“We need to advance our own technology as quickly as possible and become as self-reliant as we can,” Sung Kim, the founder of Korean AI startup Upstage, said at a press conference on Tuesday, adding that AI was now a “strategic national asset.”
Japan, for its part, is suggesting that it might turn to Anthropic’s arch-rival OpenAI to bolster its cybersecurity defenses.
How good are China’s open-source AI models?
Neither OpenAI nor Anthropic make their models available in China, including the Chinese city of Hong Kong (which sits outside Beijing’s internet controls).
Both Anthropic and OpenAI have accused Chinese labs like DeepSeek of conducting “distillation” attacks, where their models are used to train smaller, more efficient models.
Chinese models still lag models from the U.S. DeepSeek’s most recent model V4 performs at approximately the same level as Anthropic’s Claude Opus 4.6 and OpenAI’s GPT 5.4. Those models were released in February and March 2026, respectively. The Chinese startup estimated it was three to six months behind state-of-the-art frontier models.
However, while Chinese open-source models are not as powerful as their U.S.-developed peers, they are still significantly cheaper. DeepSeek’s V4 Pro cost $3.48 for 1 million tokens of output; Anthropic’s Fable 5 model cost $50 for the same output. (A token is the basic data unit that contemporary AI systems, most of which are large language models, process. It is equivalent to about a word-and-a-half of English text.)
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