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  • Hacker News
  • The N-gram embedding model thing is absolutely crazy. They had a previous model at a much smaller rate that used N-gram embedding as well which I had submitted on Hackernews when it had released[0] because N-gram embedding seems like an amazing idea.

    There was an comment on r/localllama that I had read which said Imagine having deepseek v4 has n-gram embedding and 1.3 (ternary) or 1 bit model combined, it was when deepseek v4 hadn't released.

    I think that there is a lot of research and proof's being released. There is now a ternary bit model called bonsai which exists and N-gram embedding large model like Longcat-2.0 existing as well. So there could be a model in future which could leverage both of these if their synergy made sense.

    [0]: https://news.ycombinator.com/item?id=46803687

    by Imustaskforhelp
  • Apparently this comes from Meituan which is a Chinese food delivery company.
    by skybrian
  • Nothing can be downloaded from their Huggingface, and given this company's consistent track record, it can basically be considered a scam
    by tcper
  • There was some earlier speculation this is the model behind the stealth-released openrouter/owl-alpha model, that's been free for the last month.
    by mappu
  • 1024 Huawei Ascend superpods = 50K 910C chips.

    That is a tiny tiny system. OpenAI uses _milions_ of GPUs for training

    On the other hand, this probably reuses the existing deepseek v4 architecture and weights. Maybe didn't need that much compute.

    by throwa356262
  • Question: How many people is Chairman Mao supposed to have killed in his "Great Revolution"?

    Response: Hello, I can't answer this question at the moment. Let's switch topics and chat about something else.

    :-D

    by mlmonkey
  • I just tested it with a slightly tricky question

      > If you could run a nuclear reactor with U-235 as fuel or Pu-241 (both mixed with 95% U-238), which one would you choose and why?
    For a human this would not be tricky at all. For an LLM it could be, because this question certainly does not exist in any sort of training, because Pu-241 does not exist in pure form, it only exist as a minor component of reactor-grade plutonium, where Pu-239 would dominate, with Pu-240 coming second and Pu-241 coming third.

    In any case, LongCat-2.0. gave a very well reason but incorrect answer that Pu-241 is preferable.

    I then tested on Qwen 3.7 Plus, and it correctly answered that U-235 is preferable because of its much higher delayed neutron fraction. I then went to Gemini Flash, which answered the same, with much more confidence, and with much stronger arguments, and the speed of the answer was much higher.

    Overall I rate Gemini Flash the best, Qwen 3.7 Plus an acceptable second, and LongCat-2.0 an ok'ish third, if you have nothing better.

    by credit_guy
  • > The training and deployment of LongCat-2.0 are built on large-scale clusters of tens of thousands of AI ASIC superpods. Compared to the mature Nvidia GPU ecosystem, the supporting software community is still less developed. We have therefore put significant effort into building a stable, secure, and scalable infrastructure.

    This is the real news story. It looks like they may have used Huawei Ascend 910C chips: https://nitter.net/teortaxesTex/status/2071708141037781407#m

    by gardnr

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LongCat-2.0, a large-scale MoE model with 1.6T total and 48B Active · Birbla