alt Hacker News> with all of this traffic served on Chinese AI chips
RIP Nivida shareholders
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I don't see a situation where subscription payers move outside American LLMs (chatgpt, claude, gemini)
And I don't see a situation where serious API payers are OK with handing the Chinese state all their data. Like manufactures of decades past did and learned a hard, even existential, lesson for it. The state mantra has been "Collect and Copy" for a long time now, tech just hasn't had that moment to experience it yet.
So that leaves local hosting/leasing, but one of those has totally non-practical economics and the other doesn't have enough compute to meet any kind of real demand.
I also have yet to meet a single person who isn't neck-deep in the tech space mention a Chinese LLM. It's 100% the big American three.
If anything it's custom chips from the labs that threatens Nvidia.
Another self-inflicted own courtesy of US government policy.
While I think China would always get to hardware self-sufficiency eventually, all export controls have done is (1) accelerate China's development, and (2) divert revenue that would've otherwise gone to NVIDIA/AMD/etc instead.
Ox Alpha is a smaller model and it was running very slowly. Chinese AI accelerators are coming along, but nVidia’s lead is huge.
Most US companies that have anything to do with government, finance, medical, etc. already have contractual or regulatory obligations which prevent them from using Chinese hardware or services, even before the AI boom. That's a huge market.
Nvidia will do just fine. (Disclaimer: not a shareholder. At least, not directly.)
Not really a brag: it ran like shit. Very slow (~20tps, VERY high latency) and it would timeout all the time.
I'm sure the chips are fine, but they clearly didn't have enough capacity for the demand they had (that 100T/day claim was asbolute bs)
yay, I called it! :) (in the other thread)
This is no surprise [0] [1].
>> "They are already there on open weight models and Jensen knows that it is only a matter of time until China catches up with GPUs or other AI accelerators."
It is also why Nvidia becoming a bank for other AI companies who are unable to find VCs to fund them isn't really a good thing and that is bearish.
Not really. Chinese AI companies were never using NVidia AI chips.
This announcement doesn't really mean anything at all. It means the very few people who are already using Z.ai's API will continue to do so, but the vast majority of money going to Nvidia is through the massive amount of business going to Anthropic, OpenAI, and other western cloud providers and inference providers, who are mostly using NVidia chips for inference.
Also, NVidia chips are still sold out and supply constrained.
This is the takeaway here: That's how they have been serving it at scale as Ox-Alpha. This is a definitional moment.-
Further quote:
"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."
https://z.ai/blog/glm-5.3-flash