The fight over the future of artificial intelligence took another turn Friday as Nvidia, Microsoft, Meta, Palantir, and more than 20 other technology companies urged the Trump administration to resist calls for sweeping limits on open-weight AI models. Their message is clear: restricting open-weight AI could weaken America’s position in the global AI race at the very moment Chinese competitors are gaining ground.
The letter lands just days after Chinese startup Moonshot AI drew intense scrutiny with Kimi K3, an open-weight model that topped several AI benchmarks and sparked fresh accusations in Washington that Chinese companies are benefiting from American AI research through unauthorized distillation. Instead of broad restrictions, the coalition argues that the United States should double down on openness, competition, and innovation.
The debate has exposed an unusual split inside the AI industry. Companies building open-weight models increasingly see them as the best way to accelerate innovation and broaden AI adoption. Developers of proprietary frontier models have raised concerns about security, misuse, and intellectual property, creating one of the biggest policy battles facing the AI industry this year.
Nvidia, Microsoft, Meta lead 20+ companies in push to protect open-weight AI
In the letter released Friday, the companies warned policymakers against what they described as “premature restrictions” on open-weight models, arguing that such measures could “stifle competition or drive innovation overseas.”
Open-weight AI models can be downloaded, modified, and run on an organization’s own infrastructure. That approach gives researchers, enterprises, and developers more control over how models are deployed and customized, unlike proprietary systems that operate exclusively through cloud APIs.
The coalition argues that open-weight AI offers strategic advantages beyond flexibility.
“Relying solely on closed models is not inherently safe: they can be breached, misused, or fail in ways that outsiders cannot detect,” the letter said. “And concentrating advanced AI capabilities behind a small number of closed models compounds that risk.”
The signatories contend that an open ecosystem spreads AI capabilities across universities, startups, businesses, and public institutions instead of concentrating them within a handful of companies. They say that broad participation strengthens American competitiveness rather than weakening it.
Tech giants unite behind open-weight AI as Trump weighs restrictions on Chinese models
The letter comes as Chinese open-weight models continue to improve at a pace that has surprised many in Silicon Valley. Moonshot AI’s Kimi K3 recently climbed to the top of Arena.ai’s Frontend Code Arena leaderboard, outperforming several leading American models in real-world frontend development and agentic coding tasks. That performance intensified debate over whether the United States should respond with tighter restrictions or accelerate domestic innovation.
Treasury Secretary Scott Bessent told CNBC earlier this week that the Trump administration would examine whether Chinese AI companies had stolen American intellectual property. He said the U.S. government has “the ability to sanction them because of this theft.”
The issue gained more attention after White House AI adviser Michael Kratsios alleged that Moonshot AI developed Kimi K3 by distilling Anthropic’s technology. Distillation is a widely used AI training technique in which a smaller model learns from the outputs of a larger one.
Kratsios acknowledged that legitimate AI distillation remains an important part of AI development but warned that “large-scale, covert industrial distillation aimed at stealing proprietary U.S. technology” is “unacceptable.”
Rather than banning techniques used across the industry, the coalition argues that unlawful behavior should be addressed directly.
In the letter, the companies wrote that concerns surrounding illegal distillation should be handled through “targeted legal and commercial frameworks” instead of “sweeping restrictions on techniques that play an important role in AI innovation.”
Nvidia CEO Jensen Huang and Microsoft CEO Satya Nadella both shared the letter through their personal social media accounts, signaling high-level support for its message.
Two notable names were missing from the list of signatories: OpenAI and Anthropic.
The omission comes as both companies prepare for public market debuts that could rank among the largest technology IPOs in recent years. Anthropic confidentially filed its prospectus with the U.S. Securities and Exchange Commission in June. OpenAI followed with its own confidential filing days later.
OpenAI President Greg Brockman sought to clarify the company’s position during a media briefing in New York on Thursday. He said OpenAI supports broad access to AI technology and has not participated in discussions with the Trump administration about banning Chinese open-weight models.
“I think that, that fundamentally, AI and AI usage is something that is actually very important to democratize,” Brockman said. “And so, for me, at a sort of deep level, I think that having more models, more usage, that is a good thing.”
The letter reflects a larger question facing Washington. Should the United States respond to China’s AI progress by restricting access to open-weight models, or should it encourage wider participation across the domestic AI ecosystem?
For the companies behind Friday’s appeal, the answer is straightforward.
“Our AI leadership will be judged not by one frontier AI model, but by whether the United States builds a strong, open ecosystem that diffuses into every sector,” the letter said. “This is essential for creating opportunities for innovation and prosperity across the country.”
Read the full open letter
Below is the full letter signed by Nvidia, Microsoft, Meta, Palantir, IBM, Mozilla, Hugging Face, Mistral, Perplexity, Replit, Andreessen Horowitz, and more than 20 organizations urging policymakers to support open-weight AI models.
“Open Weights and American AI LeadershipJuly 24, 2026
In the 1980s, early open-source software pioneers challenged the prevailing belief that software would advance only if companies kept tight control over their code. This movement pushed for a transparent ecosystem where developers around the world could study, modify, and improve software. Software developed by the open-source community now supports most of the internet and underlies systems used by the world’s largest technology companies, as well as the U.S. military and federal agencies conducting scientific research, cybersecurity, and other critical missions. Open source did more than lower the cost of software; it created a shared foundation of knowledge on which generations of American engineers and entrepreneurs built their institutional sovereignty.
The United States now faces a similar choice with artificial intelligence. Our AI leadership will be judged not by one frontier AI model, but by whether the United States builds a strong, open ecosystem that diffuses into every sector. This is essential for creating opportunities for innovation and prosperity across the country. It requires expanding access to AI, encouraging competition, robust application layers, and giving Americans greater control over the technology they rely on. Open weight models—AI models that anyone can download, inspect, modify, and run on their own infrastructure—are an important part of that foundation because they make advanced AI more accessible, adaptable, and widely available.
Open weights expand access to the AI economy. Startups, established businesses, universities, and public institutions can build on advanced models without training one from scratch or paying frontier-model prices for every task. Open weights let every organization match the right model to the right job at the right cost, reserving frontier-scale capability for genuine frontier problems and running efficient, specialized models everywhere else. That discipline is what will make AI economically sustainable as its use scales into the billions of everyday tasks. America wins the AI era by diffusing it into the workflows of factories, hospitals, farms, classrooms, and main street businesses.
Open weights also strengthen competition and competition is what keeps the gains of AI broadly shared rather than concentrated in a few hands. By allowing many organizations to build, adapt, and deploy advanced models, open weights create rivalry not only among model developers but across cloud chips, applications, and services. That competition spurs innovation, drives down costs, and distributes the benefits of AI broadly across our economy.
Open weights also give customers greater control. As organizations invest in AI, they want to know that they will not become locked into a single provider or lose the knowledge and capabilities they build over time. Open weight models help provide that assurance by allowing organizations to control their own data, evaluate and adapt models to their own needs, and deploy them wherever their business requirements demand. And as organizations create value with AI, open weights allow them to own that value through self-improving models, specialized capabilities, and accumulated knowledge that drive American sovereignty and prosperity.
To be sure, open weights carry real and distinct risks. Once released, the weights are beyond the original developer’s control, and modified versions are difficult to trace or reverse. But the right response to this risk is not to prohibit open weights. In a world where cybersecurity attackers use advanced AI, defenders need access to models with comparable capabilities so they can detect, simulate, and respond to emerging threats. Open models broaden defensive capability, increase transparency, and allow vulnerabilities to be discovered and remediated across many teams.
In fact, openness may be one of the most important paths to AI safety and security. Relying solely on closed models is not inherently safe: they can be breached, misused, or fail in ways that outsiders cannot detect. And concentrating advanced AI capabilities behind a small number of closed models compounds that risk. It results in a small number of single points of failure, weakens competition, and leaves critical technology in the hands of a few providers. Open weight models, on the other hand, allow a broad community of researchers and developers to examine their behavior, identify vulnerabilities, develop safeguards, and improve them over time. Just as open-source software demonstrated that transparency can be more secure than obscurity, AI safety may depend on giving more people the ability to test and strengthen the models on which society relies. It allows for rigorous benchmarking and evaluation, red teaming, and protections tied to real and demonstrated harms rather than assuming that closed systems are safer by default.
A strong AI ecosystem is not a foregone conclusion. Policymakers have an important opportunity to act. This includes expanding access to compute for startups and researchers, investing in shared training assets (datasets, tools, evaluation frameworks), and keeping the frontier plural by avoiding premature restrictions on open models that stifle competition or drive innovation overseas. These measures must also look at how strong application layers can expand sovereign use of AI across the economy.
In shaping this ecosystem, policymakers should be careful not to conflate legitimate model-development techniques with misappropriation. 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. It reflects a long tradition of learning from, building upon, and improving existing technologies, a tradition that has helped drive innovation since the rise of the open-source software movement. By contrast, unlawful efforts to extract value from closed models raise legitimate concerns. Those concerns should be addressed through targeted legal and commercial frameworks rather than sweeping restrictions on techniques that play an important role in AI innovation.
The age of AI can be one of prosperity. With the right choices, open weight AI can expand opportunity, strengthen competition, extend American technological leadership, mitigate risk, and ensure that the benefits of this extraordinary technology are shared broadly across our economy. That future is worth building, and the United States should lead in building it.
Signatories
American Innovators Network ● Andreessen Horowitz ● Arcee AI ● Arena ● Black Forest Labs ● Box ● CrowdStrike ● Dell Technologies ● Emergence Capital ● Hugging Face ● IBM ● The Linux Foundation ● Mariana Minerals ● Meta ● Microsoft ● Mistral ● Mozilla ● NVIDIA ● Palantir ● Perplexity ● Reflection ● Replit ● ServiceNow ● Telnyx ● Y Combinator”
