Comment by ls_stats

3 hours ago

America needs its own DeepSeek or Z.ai, a lot of people (myself included) root for open chinese models to win because they have no other choice.

Thinking Machines might be it.

Hopefully they'll release some smaller models (<100B) that we can run on home hardware at faster than 10tok/s.

It could be but there are a host of companies going after open weights models: Arcee, Reflection, Llama (TBD on Meta's focus on closed-source versus open-source), etc.

That said, the fine-tuning API + open weight model at least is a semblance of a viable business that could work so I will be curious about it. I'm not sure the synergy is fully there (why is someone with an open weights model privelaged to fine-tune it better if it's just QLora or Lora) but let's see!

  • > It could be but there are a host of companies going after open weights models: Arcee, Reflection, Llama (TBD on Meta's focus on closed-source versus open-source), etc.

    my bet is that Chinese government fund Chinese models way more compared to what those companies receive (except llama, which is outdated but was strong foundation at its time)

    • The story of Reflection AI is supposedly that the company was faffing and failing at winning in the coding agent space, but was introduced to Jenson, who suggested they build an open-weight model and said he would fund it. That turned into a $2 billion financing with NVIDIA doing roughly $500 million and was a complete pivot.

      I think the bet would have to be that a US Open Weight company either: 1. Gets a lot of money from Jenson who views them as a counterbalance to the big labs in his ecosystem and a way to generate leverage (the same way he is positioning neoclouds-- it also could be synergistic with neoclouds who could offer the model serving endpoints) 2. Can fast follow the same way Mistral does (which, honestly, seems like just distilling the Chinese model, which distills the US lab but is pretty innovative on a whole lot of architecture both in training and serving land.) 3. AND figure out some (maybe not super lucrative but lucrative enough) sort of business model, as well. There are lots of possible business models, so I will be curious how this whole space evolves.

      2 replies →

    • I have a similar bet. Looks like people don't like this idea. You got downvoted a lot.

What is the business model for an open weight model?

  • The same business model that Deepseek is using.

    Open-source models + services. This is more attractive because it doesn't lock in the vendors. If I grow larger, I can decide to deploy the open-source models.

    • > The same business model that Deepseek is using.

      there is a chance their business model is absorbing government funding..

    • So they're constantly hemorrhaging their most valuable clients?

      Tech history is littered with the corpses of "open source but we sell hosting" services. Models are so expensive to train, you can't be losing the big clients once they get super profitable.

  • Thinky has a potential answer in Tinker — give away the weights and charge for the SFT (and maybe RL down the line) to make the model more capable for specific tasks.

  • To compete against America. If your country has something like DeepSeek you really can't afford to let it fall as it's your best leverage if the US government decides to ban companies in your country from accessing American LLMs. And this is why there will never be a "DeepSeek of the US."

    • Considering how volatile things can get depending on who's president, I'd say even American companies need to "compete against America" if they don't want to get their rug pulled from under them (which, apparently, the legal system allows to easily happen in the US).

Also the fact that China is building solar power like crazy: that makes it fantastically more well spirited an endeavor to wish well.

Its not as good as GLM 5.2 for agentic workflows while also being bigger. Competition is going to be ruthless because the super low cost to switching.

There is also AllenAi in the US, but they have yet to produce a model at this scale. Thankfully, new contenders can come out of nowhere and do well, as long as they can produce a competitive model.

  • > Its not as good as GLM 5.2 for agentic workflows while also being bigger

    GLM 5.2 underwent extensive post-training and iteration since its original release to reach its current state. This seems like an extremely strong model for a first release, with a lot of potential for improvement, just like DS4.

    Sometimes I wish Meta had stuck with Llama 4 a bit longer to see how much further it could be pushed.