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Comment by credit_guy

2 days ago

I think the way to parse the current title "DeepSeek pause fundraise after comments on compute gap to US leaked (transcript) [pdf]" is that there was a leak that DeepSeek will pause fundraising because they perceive there is a compute gap with the US.

I am also guessing that the majority of the people who read this title will think that DeepSeek is pausing this fundraising because some comments they made about the compute gap were leaked. That is not the case.

Maybe: "Leaked Deepseek transcripts reveal plan to pause fundraising due to compute gap"

I don't know what "compute gap" means in this context though and it's not clear that that's why they plan to pause fundraising or if the title is conflating.

  • yep. the word they use is probably 克制 or self-restraint. no need to raise so much cash if you can't use it.

    in his article he talks about the negative aspects of getting everything you want. (all the money, brightest minds, biggest share in AI) etc. he says that these are the things that will cause a company to fail.

    • Unless they have a shortage of mathematicians, physicists, ... it seems a fundraiser could help bypass a compute gap by focusing even more on inference and training efficiency.

    • The maturity of leadership in China seems to be on a whole different level from the U.S.

      Lots of companies in the U.S. have fallen victim to that syndrome, but if you used the word "restraint" in that context in Silicon Valley most people would look at you like you're insane.

  • > if the title is conflating

    The title is certainly a great conflation. Any seeker of capital would want to regroup after an unfiltered leak of this magnitude, if for no other reason than to secure the forum from future leaks. The comments about the unlikelihood of enormous future profits were at least as consequential with regard to capital investment as anything else that was said.

I skimmed the doc and my impression is that your second listed interpretation -- DeepSeek is pausing investment because of a leak -- is the more correct one.

There's quite a bit of confidential information in the doc about the company and how it's positioning itself going forward to compete with US labs. I'd imagine they're not happy at all with this being leaked and are withholding investment as a punitive measure.

Not to mention the other interpretation seems illogical -- why would you pause fundraising if your perception was that you lacked resources compared to your competitors?

  • Because money isn’t free and if you know there is a chokehold in supply, why raise money ar current valuation when things are getting better by the day?

  • Maybe because if you need more money to catch up with your competitors than anticipated then your ROIC is lower and your valuation changes?

All the Chinese reporting I see point to the second (majority) interpretation. Liang being furious about his private investor talk leaked online is the news here.

e.g. https://x.com/_FORAB/status/2081034500101017616?s=20

  • Those could be subsequent developments, but that's not what the linked transcript was about. The transcript was a discussion of the DeepSeek founder (Liang Wenfeng) with investors, and he does not mention any leaks, or any frustration. He simply says that he is constrained by the supply of cards, and he has no problem of getting funding, but has no reason to raise further funding because he can't transform the cash into cards.

      > There is certainly no shortage of funds or resources --- in fact, all these are readily available [...]
    
      > Within our financial capacity, it's undoubtedly true that the more cards are always better. Our current strategy is to purchase as many cards as possible at a reasonable price --- exactly how many we can afford after using this funding round. The spending pace isn't predetermined; we'll buy whatever is available as long as prices remain competitive. In fact, I'd consider that a positive outcome if we spend the entire amount within six months. [...]
    
      > In reality, spending such a large sum is no easy task: you can't obtain enough cards, they're hard to come by [...]
    
      > Therefore, our only concern is whether we can obtain enough cards. If converting all funds into cards were feasible, we would undoubtedly do so without hesitation and are even willing to pay a premium for this benefit --- it's simply to cost effective. Even after paying the premium, however, achieving this goal remains challenging.

I wanted to post this which explains the wording but I thought the transcript was more interesting. Sorry. Maybe mods can help me to put what follows as auxiliary link. I don't know how.

https://www.bloomberg.com/news/articles/2026-07-25/deepseek-...

Update:

Less-paywalled word-for-word copy it seems at

https://fortune.com/2026/07/25/deepseek-liang-wenfeng-backer...

https://archive.ph/zpIrG

  • Most of that is paywalled, but this one paragraph in the Bloomberg article suggests it might be more to do with investors leaking information:

    "The suspension stemmed in part from Liang’s frustration over online reports about his comments to investors during his first financing deal"

    The part of the transcript I'd seen floating around online was this part from around 1 hour 26 min:

    "With the largest models available today, we simply cannot afford to train them. Even if we spent all five hundred billion yuan, we still wouldn't be able to do so. Even if we could accumulate the resources, we wouldn't have the means to utilize them. The current largest model requires approximately 800 billion activations; domestically, we are still at a scale of several dozen billion activations, and even the largest domestic model may only require several dozen billion activations—a difference of an order of magnitude. To train a model of the same size as an AI system, we would need around 50,000 GB300 GPUs or Huawei 950 GPUs, totaling two hundred thousand cards. This is merely training; research has not yet been considered. Therefore, the biggest gap between us and the United States lies in resources."

    • amusingly ive been working on ultra sparse llm inference/ training/ model design because nature loaths a dense graph/matrix and cause i think it shoukd be possible. i actually stood up a 20-25 percent faster than sota causal fast attention kernel yesterday, will be standing up cuda/metal/armv8 kernels too and thats gonna be fun.

      i genuinely think these models should be like 0.1 percent sparse for same capabilities we associate with them today, but theres no sane way to do that with extent tools. i built the right core tech for that in 2014 when there wasnt a market, but now there is and the experimentation velocity is wild.

      amusingly llms really have a hard time using my simple apis because its not in distribution array programs. but i literally stood up cpu custom memory format and micro kernel for dense causal attention in less than 24-36 hours and outperforms the equivalent fused ggml/llama cpp fast oath by like 20-25 percent

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