Beijing has discussed restricting overseas access to advanced Chinese AI models, while Washington is building a voluntary early-access review for cyber-capable systems. The approaches are not equivalent, neither implementing framework is complete, and downloadable weights make the moment before release the main point of control.
China is considering a wider security perimeter around advanced AI, extending from overseas model access to intellectual property and startup capital. The United States, by contrast, has ordered agencies to design a voluntary process for reviewing certain cyber-capable models before release. That is a consequential policy shift, but not a mirror-image export regime.
The distinction matters most for open-weight models. Governments and developers can limit who receives a model before publication; after its weights are downloaded, the developer no longer controls access through a hosted service.
Chinese authorities held meetings over roughly a month with Alibaba, ByteDance and Z.ai about potentially restricting overseas access to the country's most advanced AI models, including unreleased ones, according to an account based on three unidentified people familiar with the discussions. The Ministry of Commerce led the talks, with officials from the National Development and Reform Commission also attending.
Two of those people said participants discussed limits for both closed and more open models. One said officials also raised treating leaks or theft of proprietary AI technology as national-security offenses and restricting who can fund Chinese AI startups.
Those ideas have not become policy. Two sources said restrictions might cover only future models, and the account said officials had not decided whether or when any measure would take effect. It also could not establish how overseas access would be restricted. The ministries and companies did not respond to requests for comment.
The discussions sit alongside measures aimed at control of companies and capital. In April, China's state planner ordered Meta to unwind its $2 billion acquisition of Chinese-founded AI startup Manus. Authorities tightened oversight of outbound deals involving Chinese investors, technology, data and national security in early June, and sources said China had opened export-control investigations into Manus and other domestic AI startups that moved abroad.
Security concerns appear to be part of the policy context. Two unidentified sources said Chinese authorities were worried that Anthropic's Mythos could exploit software vulnerabilities and be deployed against Chinese interests. State media and Zhou Hongyi, founder of cybersecurity company 360, had publicly called for China to develop a comparable model. That evidence frames the proposed controls partly as a response to a perceived foreign capability, not simply an effort to preserve commercial advantage.
The companies in the talks sell products under different access models. Some Qwen, Doubao and GLM systems are closed, while others let users download, run and customize the weights. A rule can govern a provider's API or stop a future weight release; it cannot revoke copies already distributed.
That makes lost overseas adoption an economic cost of a broad restriction. Chinese models expanded globally after DeepSeek's R1 release as their capabilities improved and their prices stayed low. The account of Beijing's discussions said Z.ai's GLM-5.2 approached leading U.S. offerings at a fraction of the cost and that restrictions would probably raise costs for many businesses.
A separate administration- and industry-sourced report described GLM-5.2 as free to download and in the same performance tier as the most expensive U.S. models. That claim needs a narrow reading: the report does not identify the evaluation behind the tier comparison, and a free download does not establish the cost of deployment. The retained reporting does not quantify the hardware or operations needed to run GLM-5.2.
Nor are posted API prices an equivalent comparison. OpenAI said in its GPT-5.6 preview announcement that one million input and output tokens would cost $5 and $30 for Sol, $2.50 and $15 for Terra, and $1 and $6 for Luna. Those are charges for a vendor-run service, not estimates of the total cost to self-host GLM-5.2. The evidence supports a distribution advantage for downloadable Chinese models, but not a like-for-like cost multiple.
A June 2 executive order gave designated agencies 60 days to develop a classified process for benchmarking advanced cyber capabilities and setting the threshold for a “covered frontier model.” The designation is limited to the order's purposes; the text does not establish a general frontier-model classification system.
The agencies must also design a voluntary framework through which developers could seek a designation, give the government access to a covered model for up to 30 days before release to other trusted partners, and collaborate with officials on selecting those early users. The order says the framework cannot be read to authorize mandatory licensing, preclearance or permitting for model development or release.
The order is also a deployment policy. It directs the government to facilitate access to cybersecurity tools, including covered frontier models where appropriate, for public agencies, state and local authorities, and critical-infrastructure operators. It calls for an AI cybersecurity clearinghouse to coordinate vulnerability discovery, remediation and patch distribution. Its stated mechanism is selective early access followed by defensive use, not categorical containment.
OpenAI's preview shows how voluntary coordination can shape a launch. The company said it began GPT-5.6 with a small group of trusted partners, shared their participation with the government and took that step at the government's request while the executive-order process was being developed. It also said the arrangement should not become the long-term default and that it planned broader availability within weeks.
The company's safety case remains a company assessment. OpenAI said Sol did not cross its own Cyber Critical threshold: under the conditions of its Chromium and Firefox evaluations, the model identified bugs and components of exploits but did not autonomously produce a working full-chain exploit. It nevertheless used model refusals, real-time cyber and biology classifiers, account review, monitoring and differentiated access. OpenAI also said it spent more than 700,000 A100-equivalent GPU hours on automated red-teaming for universal jailbreaks, illustrating that a release process built around safeguards can itself require substantial infrastructure.
Washington has used stronger tools outside the new voluntary framework. In June, the government ordered that foreign nationals be denied access to Anthropic's Fable and Mythos. Anthropic initially disabled both models worldwide because it could not verify nationality in real time. Export controls on Fable were later lifted after new safeguards were added; Mythos remained available only to selected trusted U.S. organizations at the time of the reporting.
That episode demonstrates the reach of an imposed access condition, but also its bluntness: a nationality rule briefly removed the models from all users, not just the intended group. It should not be treated as a power created by the June 2 voluntary-review order.
Officials are also considering ways to restrict Chinese access to U.S. models, potentially through export controls, the administration-sourced report said. It characterized those conversations as very preliminary and said there was little agreement about measures that might work.
One more proposal is too thinly documented to carry the thesis. An access-limited brief said the administration and AI companies had discussed a capability framework for U.S. open-source models based on the current capabilities of leading Chinese open-source models. It also said the industry expected a freely downloadable Chinese model at Anthropic Mythos capability within six to 12 months. The available text does not disclose the framework's threshold, legal effect or adjustment mechanism, so it does not establish that a Chinese release would automatically set what U.S. developers may publish.
For China, the next material event is a published rule. Its text would need to show whether controls apply to hosted services, unreleased weights, company ownership, foreign funding or some combination—and which agency could enforce them. The May roundtable proposal cited in the reporting, ranging from simple filings to domestic-only access or publication bans, came from legal experts rather than the government and is not a policy announcement.
For the United States, the next evidence is the classified benchmark's practical boundary and the public design of the voluntary framework: which models qualify, what developers must disclose, how early partners are selected and whether participation remains optional in practice. Any separate open-source proposal needs enough detail to distinguish a benchmark from a release ceiling.
Until then, the available evidence supports an asymmetry. Beijing is exploring potentially broad restrictions without a disclosed mechanism. Washington has mandated the design of a narrow, voluntary cyber review while separately debating stronger measures. For open weights, both governments have the most leverage before release—but neither source package shows a workable way to restore geographic control after the files circulate.
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