4 ms·

What I dont understand is, why would a company pay $10,000s a month to anthropic for Claude in a situation where a Chinese LLM is 99% as good, is open weight an

• Arkhaine_kupo 9mo ago
  Isn't there pretty good indications that the chinese llms have been trained on top of the expensive models? Their cost is not real. Plus you have things like MCP or agents that are mostly being spearheaded by companies like Anthropic. So if it is "the future" and you believe in it, then you should pay a premium to spearhead it. You want to bet on the first Boeing not the cheapest copy of a Wright brother plane. (Full disclosure, I dont think its the future and I think we are over leveraging on AI to a degree that is, no pun intended, misanthropic)
  • malka1986 9mo ago
    > Isn't there pretty good indications that the chinese llms have been trained on top of the expensive models? So what ?
    • fc417fc802 9mo ago
      Well it raises an interesting conundrum. Suppose there's a microcontroller that's $5.00 and another that's $0.50. The latter is a clone of the former. Are you better off worrying only about your short term needs, or should you take the long view and direct your business towards the former despite it being more expensive?
      • ForHackernews 9mo ago
        You're asking whether businesses will choose to pay a 1000% markup on commodities?
      • blitzar 9mo ago
        Suppose both microcontrollers will be out of date in a week and replaced by far more capable microcontrollers. The long view is to see the microcontroller as a commodity piece of hardware that is rapidly changing. Now is not the time to go all in on betamax and take 10 years leases on physical blockbuster stores when streaming is 2 weeks away. Ai is possibly the most open technological advance I have experienced - there is no excuse, this time, for skilled operators to be stuck for decades with AWS or some other propriety blend of vendor lock-in.
        • fc417fc802 9mo ago
          This isn't betamax vs VHS. It's VHS vs a clone of VHS. The long view necessarily has to account for R&D, long term business partners, and lots of other externalities. The fact that both manufacturers will have a new model of VCR out next month, and yet another the month after that, really has nothing to do with the conundrum I gave voice to. I'll also note that there's zero vendor lock-in in either scenario. It's a simple question about the tradeoffs of indirect parasitism within the market. I'm not even taking a side on it. I don't even know for certain that any given open weights Chinese model was trained against US frontier models. Some people on HN have made accusations but I haven't seen anything particularly credible to back it up.
          • malka1986 9mo ago
            If the clone is 1/10th of the price, and of equivalent quality, why would I use the original ? I would be undercut by my concurrents if i did that, it would be a very bad business decision.
      • woadwarrior01 9mo ago
        That's a very tenuous analogy. Microcontrollers are circuits that are designed. LLMs are circuits that learned using vast amounts of data scraped from the internet, and pirated e-books[1][2][3]. [1]: https://finance.yahoo.com/news/nvidia-accused-trying-cut-deal-104241763.html https://finance.yahoo.com/news/nvidia-accused-trying-cut-dea... [2]: https://arstechnica.com/tech-policy/2025/12/openai-desperate-to-avoid-explaining-why-it-deleted-pirated-book-datasets/ https://arstechnica.com/tech-policy/2025/12/openai-desperate... [3]: https://www.businessinsider.com/anthropic-cut-pirated-millions-used-books-train-claude-copyright-2025-6 https://www.businessinsider.com/anthropic-cut-pirated-millio...
        • fc417fc802 9mo ago
          > Microcontrollers are circuits that are designed. LLMs are circuits that learned using vast amounts of data So I suppose the AI companies employ all those data scientists and low level performance engineers to what, manage their website perhaps? It's poor form to go around inserting your pet issue where it isn't relevant.
      • FridgeSeal 9mo ago
        Well the company of the former microcontroller has gone out of their way to make getting and developing on actual hardware as difficult and expensive as possible as possible, and could reasonably accused of doing “suspect financial shenanigans”, and the other company will happily sell me the microcontroller for a reasonable price. And sure, thy started off cloning the former, but their own stuff is getting really quite good these days. So really, the argument pretty well makes itself in favour of the $0.5 micro controller.
    • antonvs 9mo ago
      It would mean that their costs are lower than they would be to achieve the same capabilities otherwise.
  • blitzar 9mo ago
    > Isn't there pretty good indications that the chinese llms have been trained on top of the expensive models? there are pretty good indications that the american llms have been trained on top of stolen data
    • svara 9mo ago
      This is proven. You can prove it yourself easily. Take a novel from your bookshelf, type in any sentence from the novel and ask it what book it's from. Ask it for the next sentence. This works with every novel I've tried so far in Gemini 3. My actual prompt was a bit more convoluted than this (involving translation) so you may need to experiment a bit.
  • re-thc 9mo ago
    > Their cost is not real. They can’t even officially account for any nvidia gpus they managed to buy outside the official channels.
  • ForHackernews 9mo ago
    This so-called "PC compatible" seems like a cheap copy, give me a real IBM every time.
  • zozbot234 9mo ago
    > Isn't there pretty good indications that the chinese llms have been trained on top of the expensive models? How do you even do that? You can train on glorified chat logs from an expensive model, but that's hardly the same thing. "Model extraction" is ludicrously inefficient.
    • Arkhaine_kupo 9mo ago
      > How do you even do that? I am not going to comment on how they did it. But they were openly accused by OpenAI of it. I believe the discussion is over destillation vs foundational models. https://www.jdsupra.com/legalnews/openai-accuses-deepseek-of-unlawful-use-2896277/ https://www.jdsupra.com/legalnews/openai-accuses-deepseek-of... There are other theories like OpenAI inflated their training costs to seek further investment in later growth quarters. Meanwhile Deepseek under reported their cost to portray China as more cost efficient investment. If that was the case then their performance is similar, with similar training costs but one side reported even the coffee from the coffee machine in the office in the total while the other only counted the minimal CPU cycle cost and not the GPU, energy, engineering etc. Which is plausible too. I have no dog in the fight but the first accusation seemed quite serious, hence why I asked
• re-thc 9mo ago
  How do they run on US servers? Self host? That’s not going to be cheap whilst the big AI players horde resources like memory.
  • Topfi 9mo ago
    There are many providers (Fireworks, Groq, Cerebras, Google Vertex), some using rather common hardware from Nvidia, etc., others their own solutions focused solely on high throughput inference. They often tend to be faster, cheaper and/or more reliable than what the lab that trained the model is charging [0], simply because there is some competition, unlike with US frontier models which at best can be hosted by Azure, AWS or GCloud at the same price as the first party. [0] https://openrouter.ai/moonshotai/kimi-k2-thinking https://openrouter.ai/moonshotai/kimi-k2-thinking
    • re-thc 9mo ago
      And who funds those providers? They can clearly pull the plug any time. The so called many providers is the same group under the hood. Nvidia was noted as having most of their revenue heavily tilted against only a few major customers for example.
      • Topfi 9mo ago
        I don’t really understand your point. A company offering only inference will inherently always have lower costs and require less hardware than one that both provides inference and does training of new models.
        • re-thc 9mo ago
          The point is it doesn't work like that. Check out all the special purpose vehicles, loans and fund raises going around in that space. Deals claiming for $x billion in funds only got millions + GPU rentals in special deals. And the offering of those deals still hinges on the top 3 said customers buying to float things up. i.e. whether you go for "only inference" or "both" it'll work out similar somewhere.
• willis936 9mo ago
  By what metrics are they 99% as good? There are a lot of benchmarks out there. Please share them. I think the answer lies in the "we actually care a lot about that 1% (which is actually a lot more than 1%)".
  • Topfi 9mo ago
    I'm still testing myself and cannot make a confident statement yet, but Artifical Analysis is a solid and independent, though also to be fair somewhat imperfect source for a general overview: https://artificialanalysis.ai/ https://artificialanalysis.ai/ Purely according to Artificial Analysis, Kimi K2.5 is rather competitive in regard to pure output quality, agentic evals are also close to or beating US made frontier models and, lest we forget, the model is far more affordable than said competitors, to a point where it is frankly silly that we are actually comparing them. For what it's worth, of the models I have been able to test as of yet, when focusing purely on raw performance (meaning solely task adherence, output quality and agentic capabilities; so discounting price, speed, hosting flexibility), I have personally found the prior Kimi K2 Thinking model to be overall more usable and reliable than Gemini 3 Pro and Flash. Purely on output quality in very specific coding tasks, Opus 4.5 was in my testing leaps and bounds superior of both the Gemini models and K2 Thinking however, though task adherence was surprisingly less reliable than Haiku 4.5 or K2 Thinking. Being many times more expensive and in some cases less reliably adhering to tasks, I really cannot say that Opus 4.5 is superior or Kimi K2 Thinking is inferior here. The latter is certainly better in my specific usage than any Gemini model and again, I haven't yet gone through this with K2.5. I try not to just presume from the outset that K2.5 is better than K2 Thinking, though even if K2.5 remains at the same level of quality and reliability, just with multi modal input, that'd make the model very competitive.
  • samuelknight 9mo ago
    Open models have been about 6 to 9 months behind frontier models, and this has been the case since 2024. That is a very long time for this technology at it's current rate of development. If fast takeoff theory is right, this should widen (although with Kimi K2.5 it might have actually shortened). If we consider what typically happens with other technologies, we would expect open models to match others on general intelligence benchmarks in time. Sort of like how every brand of battery-powered drill you find at the store is very similar, despite being head and shoulders better than the best drill from 25 years ago.
• eru 9mo ago
  Usain Bolt's top speed is about 44.72 km/h. My top speed sprinting is about 25 km/h. That's at least 50% as good. But I'd have a hard time getting paid even half as much as Mr Bolt.
  • SecretDreams 9mo ago
    Yeah, but you'd both be quite suitable to go walk to the grocery store.
    • eru 9mo ago
      Sure, but that would be a waste of Mr Bolt's capability for locomotion.
  • solumunus 9mo ago
    Even someone with marginally less top speed isn’t getting paid half as much as Usain Bolt. Athletes aren’t getting paid per unit of output. This analogy is not analogising.
    • eru 9mo ago
      No, no, you understood it exactly right: someone who's 99% as fast as Usain Bolt doesn't get 99% as much attention and money either.
      • solumunus 9mo ago
        Which doesn’t even slightly apply to what you’re drawing the analogy against. Your attempted analogy is invalid.
  • atwrk 9mo ago
    OK but what if, staying in that analogy, you just have to wait 6-12 months to become as fast as Usain is right now?
    • falcor84 9mo ago
• energy123 9mo ago
  I tried that but I'm back to paying OpenAI $200/month because the quality was significantly worse on my codebase.
• senko 9mo ago
  As a heavy Claude Code user, I would like to have that option. But if it's just 33% as good, I wouldn't bother. Top LLMs have passed a usability threshold in the past few months. I haven't had the feeling the open models (from any country) have passed it as well. When they do, we'll have a realistic option of using the best and the most expensive vs the good and cheap. That will be great. Maybe in 2026.
  • fy20 9mo ago
    GLM-4.7 is pretty good. It is not as good as Opus 4.5 though. If you are a business there is no point trying to save $50 a month, as the cost of the engineers time is much greater.
• Lerc 9mo ago
  I don't think 99% of the best is a good metric. It is highly dependent on what the best represents. If you had a 100% chance of not breaking your arm on any given day, what kind of value would you place on it over a 99% chance on any given day. I would imagine it to be pretty high. The top models are not perfect, so they don't really represent 100% of anything on any scale. If the best you could do is have a 99% chance of not breaking your arm on any given day, then perhaps you might be more stoic about something that is 99% of 99% Which is close enough to 98% that you are 'only' going to double the number of broken arms you get in a year. I suspect using AI in production will be a calculated more as likelihood of pain than increased widgets per hour. Recovery from disaster can eat any productivity gains easily.