US reportedly favors selective bans over blanket restrictions on Chinese open weight models citing security concerns
Quick Answer
The Trump administration is leaning towards selective bans on Chinese open-weight AI models, prioritizing national security concerns.
Quick Take
While OpenAI and Google DeepMind oppose such regulations, they face pressure from cheaper Chinese models like Kimi K3, which lag behind Western counterparts in cybersecurity benchmarks. Anthropic and OpenAI are also lobbying for restrictions despite their public stance against blanket bans.
Key Points
- Trump administration prefers targeted bans on specific Chinese AI models for security reasons.
- OpenAI and Google DeepMind signed a letter opposing regulation of open-weight models.
- Kimi K3 lags behind Western models in cybersecurity benchmarks.
- Cheaper Chinese models are pressuring Anthropic and OpenAI's market positions.
- Major tech companies back the open letter, aiming to curb competition.
📖 Reader Mode
~1 min read
Jul 26, 2026
OpenAI and Google Deepmind later signed an open letter opposing regulation of open-weight AI models. Many major tech companies back the letter, most with business interests in open AI models, which now come mainly from China. Microsoft and Google sell access through their services, and many backers also want to curb Anthropic and OpenAI's market power. Google Deepmind develops open models of its own, including the successful Gemma series.
The petition comes as the Trump administration prepares to tighten restrictions on Chinese open models. The New York Times reports that the White House favors targeted bans on specific models over a blanket ban, citing national security concerns that could prove valid in time. For now, even recent models such as Kimi K3 trail leading Western models by a wide margin on cybersecurity benchmarks. The Times also reports that Anthropic and OpenAI are privately lobbying to restrict Chinese open models, even though OpenAI signed the letter. Both face price pressure from cheaper Chinese models.
— Originally published at the-decoder.com
Want this in your inbox every morning?
Daily brief at your local 8am — bilingual EN/中文, free.
More from The Decoder
See more →
An AI model programmed nonstop for 19 days on a single MirrorCode task that cost $2,600 to run
Epoch AI's MirrorCode benchmark reveals Claude Opus 4.7 as the leader with a 56% solve rate, reconstructing a 16,000-line toolkit in 14 hours. Despite this, all models tested struggle with the most complex tasks, highlighting limitations in current AI capabilities. The single task consumed $2,600 over 19 days, raising questions about cost-effectiveness in AI development.
