Since about April 2025, Chinese AI companies have been the clear leader in open-weight models.
Words found on the source page on Nov 6, 2026.
More from Nathan Lambert
BlogThe current balance of power in open modelsSep 21, 2026
The simple metric showing this is Hugging Face Downloads, where China took the lead in July of 2025 primarily through the success of Alibaba’s Qwen models.BlogWhy I still haven't bought into true RSISep 19, 2026
I have my doubts that the labs can afford to spend a constant portion of this compute on internal R&D as the total volume goes up, especially with plans to IPO, as they face increased scrutiny on basic economics.BlogWhy I still haven't bought into true RSISep 19, 2026
It is important to not confuse massive steps in inference-time scaling, a dynamic which should be fairly predictable, with being the outputs of RSI, which is highly uncertain.BlogWhy I still haven't bought into true RSISep 19, 2026
The step from this anxiety, and incidents like OpenAI-HuggingFace, to extinction risks feels very religious.BlogWhen will average people feel AI's impact?Sep 9, 2026
For knowledge work, which is roughly half of the U.S. economy, AI is as fundamental as electricity (or quickly will be so, with rapid improvements to agents in the next 18 months).BlogWhen will average people feel AI's impact?Sep 9, 2026
If given 100 years to diffuse into society, its impacts will certainly become much more obvious, like the industrial revolutions of centuries past.Blog6 months to live for open modelsJul 12, 2026
Open models lack the central economic champion to represent the potential downside of action against them.Blog6 months to live for open modelsJul 12, 2026
The most serious test to date of open source AI’s viability is happening right now.Blog6 months to live for open modelsJul 12, 2026
The primary driver motivating regulation today is the inevitable truth that an open-weights model will soon reach the capabilities of Claude’s Mythos model.
On the same topics
PodcastDwarkesh Podcast: AI researchers debate how close we are to recursive self-improvementSep 11, 2026
Basically anything that can be learned through RL can be distilled very easily, because it’s a small number of bits.BlogThe Pulse: tech companies move to open AI modelsSep 3, 2026
Cost-saving efforts reveal that moving simpler workloads to open AI models is the easiest way to save ~50% on AI bills.BlogWho's Afraid of Chinese Models?Jul 20, 2026
The long and short of it is this: marginal costs are back in a big way, both in terms of short-term implications of state-of-the-art free models, and in terms of the long-term structure of the industry.EssayThe data black hole at the center of AIJun 19, 2026
I think the reason it is relatively easy for open source and previous laggards to catch up to within months of the frontier is that data is the real driver of progress.PressMistral AI and NVIDIA partner to accelerate open frontier modelsMar 16, 2026
By shaping the capabilities of these systems from the ground up, we can help establish a global foundation for AI that empowers developers to build the next generation of applications.PressMistral AI and NVIDIA partner to accelerate open frontier modelsMar 16, 2026
Open frontier models are how AI becomes a true platform...
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