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How GLM built its own inference infrastructure

411 points · 285 comments · whiteros_e

  1. zicohacks · · focus · HN ↗
    US chip export restrictions may actually be an advantage for China's AI Infrastructure. Chinese companies are forced to speed up developing their own AI chips
    1. HarHarVeryFunny · · focus · HN ↗
      China themselves recognize this. After Trump relaxed sanctions and allowed NVIDIA H200 sales to China on a case by case basis, the Chinese government stepped in to essentially block it!

      In addition to Huawei who make the Ascend series that Ziphu are using, there are also at least a half dozen or so other Chinese companies also making their own AI accelerators.

      1. 0xbadcafebee · · focus · HN ↗
        And this wouldn't have happened if we had tried to get them to buy our hardware rather than trying to gatekeep. Protectionism never works in the long term.
        1. freakynit · · focus · HN ↗
          US companies should now be more worried about Chinese companies flooding the market with their, hopefully, very affordable GPU's. The scale at which they can manufacture stuff is unmatched anywhere else. Nvidia can kiss goodbye to their 75%+ profit margins.

          Almost everyone knew that these sanctions would backfire within a few years. You can't really put sanctions that have noticeable negative effects on bigger economies. They only work for small to medium economies. I believe sanctions on any economy in top 10 would fail.

          1. aurareturn · · focus · HN ↗
            China is gated by not having EUV machine access. They're also bottlenecked by ASML's DUV machine production like everyone else. There are already talks of banning China from even purchasing DUV machines from ASML.

            So until China solves the ASML problem, there won't be any flooding.

            1. Catloafdev · · focus · HN ↗
              >until China solves the ASML problem

              Which they are in progress on: <a href="https:&#x2F;&#x2F;www.reuters.com&#x2F;world&#x2F;china&#x2F;how-china-built-its-manhattan-project-rival-west-ai-chips-2025-12-17&#x2F;" rel="nofollow">https:&#x2F;&#x2F;www.reuters.com&#x2F;world&#x2F;china&#x2F;how-china-built-its-manh...

              1. aurareturn · · focus · HN ↗
                Yes, but we don&#x27;t know how well they work or what nm can they print or how machines they can make.
                1. HarHarVeryFunny · · focus · HN ↗
                  They&#x27;ve overcome every hurdle to go from nothing to having working machines, so all these questions are presumably a matter of how fast they will improve and ramp up production (initially 5 this year, 20 next year), not whether they will.

                  China have been really squeezing all they can out of DUV machines, but I&#x27;m not sure how much node size really matters for AI competition - more of a cost issue (more chips&#x2F;power for same FLOPs) than anything, and TSMC &amp; NVIDIA&#x27;s healthy profit margins need to be considered too.

                  1. aurareturn · · focus · HN ↗
                    I&#x27;m well aware of how good China is at manufacturing. However, DUV&#x2F;EUV machine manufacturing is unproven.

                    What is the timeline like? 1 year? 5 years? 10 years?

                    1. HarHarVeryFunny · · focus · HN ↗
                      They already have working machines, and are slated to ship the first 5 early production ones right about now (before the end of 2026), and are projecting 20 for next year.

                      Small numbers perhaps, but this is happening right now.

                      What will the numbers be in 5-10 years time? Who knows, but ASML took about 5 years to go from 20&#x2F;yr to 100+&#x2F;yr.

                      Of course politically the world may well be quite different in 5 years time, as may be the AI market.

                      1. aurareturn · · focus · HN ↗
                        Yes, 5 years seems like an eternity in AI world.

                        We also don&#x27;t know how small of nm chips they can manufacture. If it&#x27;s 20nm, it&#x27;s practically useless for advanced AI chips.

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