As US weighs response to Chinese AI, industry urges against broad open-weight restrictions

# As US weighs response to Chinese AI, industry urges against broad open-weight restrictions | TechCrunch Source: [https://techcrunch.com/2026/07/24/as-us-weighs-response-to-chinese-ai-industry-urges-against-broad-open-weight-restrictions/](https://techcrunch.com/2026/07/24/as-us-weighs-response-to-chinese-ai-industry-urges-against-broad-open-weight-restrictions/) Several AI companies, including Hugging Face, Meta, Microsoft, Mistral, and Nvidia, have signed an[open letter](https://www.microsoft.com/en-us/corporate-responsibility/topics/open-weight/)urging policymakers not to impose broad “premature restrictions” on open\-weight AI models\. The letter comes as Washington debates how the U\.S\. should respond to allegations that Chinese AI labs are stealing intellectual property from their American counterparts, and growing in capability\. The letter doesn’t mention China at all, but it comes in the wake of reports that the Trump administration has been considering banning Chinese open\-weight models, and potentially[issuing sanctions against AI](https://techcrunch.com/2026/07/22/treasury-threatens-sanctions-after-white-house-claims-moonshot-distilled-anthropics-fable/)companies from the country\. The White House has even accused Moonshot AI of distilling Anthropic’s Fable model to train its recently released and, by all measures, very impressive,[Kimi K3 model\.](https://techcrunch.com/2026/07/18/kimi-threat-or-menace/) The missive appears to be aimed at discouraging a total ban on Chinese models, as well as ensuring the administration’s response to alleged Chinese distillation doesn’t spill over into broader restrictions on open\-weight AI or common techniques like distillation: > 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\. Or as Amjad Masad, CEO of Replit \(which also signed the letter\), told TechCrunch: “I think banning Chinese open models is as good as banning open models in general\.” He pointed out that[Thinking Machines Lab’s new open model, Inkling](https://techcrunch.com/2026/07/15/thinking-machines-amps-up-its-bet-against-one-size-fits-all-ai-with-its-first-open-model-inkling/), was trained with the help of Moonshot’s Kimi 2\.5\. “It’s an ecosystem, and the precedent \[a ban would\] set is bad\.” The letter also pushes back on arguments in the industry that[open\-weight models are inherently dangerous](https://techcrunch.com/2026/07/22/arcee-a-us-open-source-ai-lab-says-chinese-models-are-not-inherently-dangerous/)because they expand access to powerful models, which can be used in cyberattacks or other nefarious activities, without any oversight\. “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,” the letter reads\. “Open models broaden defensive capability, increase transparency, and allow vulnerabilities to be discovered and remediated across many teams\.” Last week, OpenAI disclosed that while testing GPT\-5\.6 Sol and another unnamed model, one of the[systems exploited a weakness](https://techcrunch.com/2026/07/22/how-an-openais-human-mistake-led-to-the-ai-powered-hack-on-hugging-face/)in its testing environment to[access a Hugging Face repository](https://techcrunch.com/2026/07/21/openai-says-hugging-face-was-breached-by-its-pre-release-models/)containing a solution to a coding benchmark\. One could argue the model’s goal wasn’t malicious, and that it was effectively cheating on a test to get the highest score\. But the incident sparked debate about the risks of concentrating advanced AI technology behind a handful of closed providers\. Hugging Face[said](https://x.com/ClementDelangue/status/2079253659108409587)it was not able to defend itself against the attack with commercial frontier AI models because their guardrails blocked its efforts\. The closed AI models it used were unable to distinguish between being asked to build exploits for an attacker and a defender trying to detect them\. The company instead had to pivot to using Chinese AI firm Z\.ai’s GLM 5\.2, a powerful open\-weight model, to defend itself against the attack\. The letter highlights a divide in the AI industry\.[Companies like OpenAI](https://techcrunch.com/2026/07/20/openai-is-scared-of-open-weight-models-should-the-us-be/)and Anthropic have urged the administration to respond to alleged IP theft by Chinese AI firms as open\-weight models grow rapidly in capability\. The outcome could have major implications on their business models, which is being threatened by the spread of cheap, highly capable, and accessible AI models\. These companies, alongside other closed source AI developers like Google DeepMind and SpaceX, are notable in their absence at the bottom of this letter\. Those who signed the letter have an obvious economic stake in seeing open AI models flourish\. Companies like Nvidia, Microsoft Azure, and other infrastructure providers have a vested interest in pushing for commoditized models: If models are interchangeable, people will buy more GPUs, rent more cloud capacity, build more applications, and use more routing layers\. The letter encourages policymakers to expand access to compute for startups and researchers; invest in shared training assets like datasets, tools, and evaluation frameworks; and “\[keep\] the frontier plural by avoiding premature restrictions on open models that stifle competition or drive innovation overseas\.” *This article has been updated with comment from Amjad Masad, CEO of Replit\.* *When you purchase through links in our articles,[we may earn a small commission](https://techcrunch.com/techcrunch-affiliate-monetization-standards/)\. This doesn’t affect our editorial independence\.* Rebecca Bellan is a senior reporter at TechCrunch where she covers the business, policy, and emerging trends shaping artificial intelligence\. Her work has also appeared in Forbes, Bloomberg, The Atlantic, The Daily Beast, and other publications\. You can contact or verify outreach from Rebecca by emailing[rebecca\.bellan@techcrunch\.com](mailto:[email protected])or via encrypted message at rebeccabellan\.491 on Signal\. [View Bio](https://techcrunch.com/author/rebecca-bellan/)