Nvidia, Meta and Microsoft have joined 22 other organizations in urging U.S. policymakers not to impose sweeping controls on open-weight AI models, warning that broad restrictions could weaken American leadership as competition with China intensifies.

The coalition said it supports targeted legal and commercial action against intellectual-property theft and other proven misuse, rather than restrictions that would cover technologies used for legitimate AI development. The open letter’s signatories include IBM, Palantir, Mistral, Hugging Face, Mozilla, Andreessen Horowitz and the Linux Foundation.

Open-weight models allow businesses, researchers and governments to download software, customize it and run it on their own infrastructure. According to the letter, that access makes advanced systems easier to adapt while giving organizations more control over their data, security and computing environments.

The companies argued that open and closed systems should not be treated as opposing models, but as necessary parts of the AI market. They said open models support competition, reduce deployment costs and give developers more freedom to inspect or modify the technology they use.

Open models remain central to U.S. AI competition

Nvidia CEO Jensen Huang shared the letter in his first post on X and defended a market in which both development approaches can coexist. Huang said open models support cybersecurity, safety, national control and the wider use of AI tools across industries.

“For my first post, I’m sharing a letter NVIDIA signed on why open models matter…The world needs both frontier closed models and frontier open models.”

Elon Musk also supported the letter in a reply to Huang’s post. Musk’s xAI develops Grok, a chatbot that competes with products from OpenAI and Anthropic, although xAI was not identified among the 25 signatories listed in media reports.

This has my full support. Jensen is right. — Elon Musk (@elonmusk) July 24, 2026

The companies issued their warning as the Trump administration considers action against Chinese AI developers accused of using American technology without authorization. U.S. Treasury Secretary Scott Bessent said this week that officials would examine whether Chinese models had been trained through unauthorized use of outputs from U.S.-built systems.

According to Bessent, sanctions and Entity List restrictions could apply if Chinese companies carried out industrial-scale distillation that crossed into intellectual-property theft. He also said the administration supports open-source AI, distinguishing lawful development practices from alleged attempts to copy protected American technology.

Distillation refers to the use of one model’s output to help train or improve another system. In their letter, Nvidia and the other signatories described the method as a common tool for model improvement, evaluation and validation, while cautioning policymakers against treating every use of it as theft.

“Distillation, or the practice of using one model’s outputs to help train or improve another, is a widely used technique for model improvement, evaluation, and validation.”

That distinction is central to the coalition’s argument. If policymakers define distillation or open-weight access too broadly, the companies warned, enforcement aimed at alleged theft could also affect ordinary model testing, improvement and deployment by legitimate users.

Drawing on the history of open-source software, the coalition argued that developers have long learned from existing systems and used shared tools to build new products. The signatories said authorities should pursue proven legal violations directly without blocking techniques used by legitimate researchers and companies.

China’s recent progress has added pressure to the policy debate. Moonshot AI’s Kimi K3 reached first place on the Frontend Code Arena, according to the benchmark, placing a Chinese model ahead of several established U.S. products in that category.

Former White House AI and crypto adviser David Sacks has warned that such gains could threaten the U.S. position in the AI race. U.S. officials have separately accused Moonshot of distilling Kimi K3 from Anthropic’s Fable model, though Moonshot’s alleged conduct remains part of the policy dispute rather than an established finding, according to Reuters.

Human oversight and spending risks remain in focus

The debate over open models has developed alongside broader questions about how companies and traders should use AI. As crypto.news reported on July 24, Gate founder and CEO Dr. Han supported using AI to collect information and study market signals while leaving final trading decisions to people.

During an episode of the Gatecast podcast, Dr. Han said automated tools could help users navigate millions of digital assets and tens of thousands of decentralized applications. However, he said traders must review the information produced by those systems before acting on it.

“AI + human intelligence” will become a more effective approach in the future, Dr. Han said.

That position places AI in an assistant role rather than giving automated systems full control over investment decisions. According to Dr. Han, machines can process large quantities of market data quickly, while human judgment remains necessary when users assess risks and decide whether to trade.

Financial concerns have also followed the rapid expansion of AI infrastructure. Earlier in July, former Fidelity fund manager George Noble warned that a collapse in the AI investment boom could cause 17 times more damage than the dot-com crash, which erased about $5 trillion from the Nasdaq.

Noble tied that risk to the large amount of capital flowing into data centers, chips and related infrastructure. According to the former fund manager, losses could spread beyond technology companies if expected returns fail to cover the money committed to AI development.

“The fallout from this could really be much more significant,” Noble said while discussing rising AI capital expenditure.

While Noble’s warning concerns financial exposure rather than open-weight regulation, both debates share a central policy question: how the U.S. can manage risks without halting useful development. Nvidia and its fellow signatories argued that focused enforcement offers that balance, allowing authorities to pursue theft or misuse while preserving access to open AI technology.