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menaerustoday at 12:39 PM3 repliesview on HN

It was evident that this will happen.

> Compared with our initial baseline on the same hardware, we achieved a 3× improvement in end-to-end serving performance, reaching hardware efficiency and per-token cost comparable to mainstream NVIDIA GPUs. This demonstrates that Chinese chips can support frontier-model inference efficiently and economically at scale.


Replies

verdvermtoday at 2:05 PM

you can also derive some stats from the ~10T tokens a day on 100k devices, 100M / device / day, but then one has to account for the multi-gpu model size, and I need coffee before I go there

HSOtoday at 4:04 PM

> It was evident that this will happen.

ok, show it

i`ve recorded a few people who saw this coming in 2022 and i can tell it wasnt many

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gpt5today at 3:18 PM

I’ll just note that NVidia’s moat has never been inference, and there are many chips used at a much larger scale than Chinese chips for inference like TPUs and AMD chips.

The other part is that it’s a bit of a meme here to say that the chip restriction is actually helping China (or shall I say, coordinated effort?). For once, we know that China has put a lot of pressure on the US to relax these controls multiple times. In addition to large chip smuggling networks (e.g. 22% of NVidia’s worldwide revenue magically comes from Singapore, and the ratio has been growing).

Lastly, assuming acceleration in AI (which we ARE seeing), there might not be time to China to catch up. The best estimate right now is that the first EUV chips from China will not come out before 2030. By that time who knows how powerful AI will be.

All I’m saying is that the discussion is so one sided and a bit baselesss with no nuance, that it seems either a meme/groupthink in the community or coordinated. If anything, the data suggests that the US should increase its export controls and better track the tech supply chain if it wants to further curb Chinese progress.

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