@Suhail: https://x.com/Suhail/status/2101665324882075958
Summary
Nathan Lambert predicts that top Chinese AI labs are increasingly using Huawei chips for inference and Nvidia for training, which will accelerate with the rise of agent swarms and scaled post-training.
View Cached Full Text
Cached at: 09/20/26, 09:24 PM
🎯
Nathan Lambert (@natolambert): My best guess is that for scaled RL most of the top Chinese AI labs are starting to use a lot of Huawei for inference and Nvidia for training (maybe not for weird architectures). As agent swarms, even more scaled post-training, etc becomes the norm, this will accelerate their
Similar Articles
Chinese companies are ditching Nvidia’s advanced accelerators for domestic AI suppliers
Chinese companies are increasingly allocating AI accelerator budgets to domestic suppliers like Huawei and Hygon, reducing reliance on Nvidia amid US-China tensions. A Bloomberg survey shows 46% of spending will go to domestic products in the next year, up from 30%.
@rohanpaul_ai: Opinion from a former Meta PM. And this is from Aravind Srinivas of Perplexity "China can build data centers a lot fast…
A discussion about the risk of Chinese open-source AI models gaining market share and being optimized on Huawei chips, while the US lags in data center construction, as highlighted by Aravind Srinivas and Xiaoyin Qu.
China's Huawei says AI chip demand outstrips supply as it steps up Nvidia challenge
Huawei reports that demand for its AI chips exceeds supply, highlighting its growing challenge to Nvidia in the AI hardware market.
Buying AI accelerators/GPUs in China...
A user asks about buying Chinese AI accelerators/GPUs for inference, specifically looking for Huawei alternatives to Nvidia, with support for vLLM or Llama.cpp.
@ohlennart: hm...
Chris McGuire discusses the Huawei Chairman's admission of constraints in China's AI chip production, highlighting long-standing concerns about Huawei's limited capacity for domestic and international AI compute.