4 ms·

A month ago I wrote a blog post about how Hy3 was topping the OpenRouter rankings despite no one talking about it: https://news.ycombinator.com/item?id=48317294

• Miner49er 3mo ago
  I had to stop using it because I was getting rate limited like crazy. Probably why it has dropped. Seemed like they couldn't keep up with demand.
• andai 3mo ago
  That was the preview model right? This one appears to be significantly better. I mean it's still a small model, but at least the benchmark scores (incl. on DeepSWE) went up significantly. It costs as much as Flash, but the benchmarks are on par with Pro (or above in some cases). Of course, benchmarks are mostly meaningless -- the only real benchmark is the actual work you give it :)
• BoorishBears 3mo ago
  Writes pretty engaging prose, finetunes well, now MIT licensed... what's not to like? Oh and very good world knowledge for the size: better than than DS4 Flash
  • Azantys 3mo ago
    Do people really use 100B+ models for writing? I am no writer but to me it seems like writing is one of the easiest tasks with barely any logic or reasoning and as long as its not longer than a handful of pages I expect even 8B models to perform great.
    • BoorishBears 3mo ago
      The largest model I've post-trained in the last 2 years of working on this problem was Kimi 2.5 at 1T parameters. The simplest way I'd put it is, teaching a model to write coherently (follow rules, patterns, etc.) is easy enough: just use teacher forcing. Teaching a model to write creatively is easy enough: just use RL and punish it for not being creative. Teaching a model to write well and creatively takes learning two partially opposing objectives that spike the learning requirements in ways that smaller models really struggle with.
      • fc417fc802 3mo ago
        > is easy enough: just use RL and punish it for not being creative. How are you scoring creativity in an unsupervised manner? That seems anything but easy.
        • BoorishBears 3mo ago
          Did you try reading the whole comment? Once creativity is being measured in isolation, getting multiple responses from the model is enough to measure creativity a ton of different ways: wordfreq to identify overused phrases, getting multiple responses for the same prompt and promoting the least similar as preferred for policy optimization, etc. But that's of limited use for stuff like getting diverse names and such. You want creativity and coherency, and if you just punish the model for using an overused phrase, the first thing it does is strongly learn a new overused phrase (or gibberish). (Also I don't think you mean unsupervised. You probably mean without humans [since LLMs struggle to judge creativity], but that's not what unsupervised means.)
          • fc417fc802 3mo ago
            I did read the the full comment and I did in fact mean exactly what I wrote when I used the term "unsupervised". I think the condescension does nothing but get in the way. Try extending the benefit of the doubt. > enough to measure creativity a ton of different ways ... The things you listed seem more like temperature than creativity to me. At this point it occurs to me that this is likely yet another case of highly misleading technical jargon. Suffice to say that truly creative writing requires something entirely different than unusual sentence structure - in fact it doesn't require unusual phrasing at all. Re unsupervised, it seems the misunderstanding here follows naturally from the previous difference in word meaning. Hopefully you see the difficulty of scoring long form answers for the creativity of the underlying ideas, as well as the impossibility of using a labeled dataset to train on such a criteria.
• terhechte 3mo ago
  It is really slow on openrouter and I ran into many http errors.
• jubilanti 3mo ago
  Because it was free with generous limits and high availability, until it wasn't.