EDIT: Also checked the chats they shared, and the thinking process is very similar to the raw (not the summarized) Gemini 3 CoT. All the bold sections, numbered lists. It's a very unique CoT style that only Gemini 3 had before today :)
I genuinely hope that gemini 3 flash gets open sourced but I feel like that can actually crash the AI bubble if something like this happens because I genuinely feel like although there are still some issues of vibing with the overall model itself, I find it very competent overall and fast and I genuinely feel like at this point, there might be some placebo effects too but in reality, the model feels really solid.
Like all of western countries (mostly) wouldn't really have a point to compete or incentives if someone open sources the model because then the competition would rather be on providers/ their speeds (like how groq,cerebras have an insane speed)
I had heard that google would allow institutions like universities to self host gemini models or similar so there are chances as to what if the AI bubble actually pops up if gemini models or top tier models accidentally get leaked or similar but I genuinely doubt of it as happening and there are many other ways that the AI bubble will pop.
My most important takeaway is that, in theory, I could get a "relatively" cheap Mac Studio and run this locally, and get usable coding assistance without being dependent on any of the large LLM providers. Maybe utilizing Kimik2 in addition. I like that open-weight models are nipping at the feet of the proprietary models.
So Harmony? Or something older? Since Z.ai also claim the thinking mode does tool calling and reasoning interwoven, would make sense it was straight up OpenAI's Harmony.
> in theory, I could get a "relatively" cheap Mac Studio and run this locally
In practice, it'll be incredible slow and you'll quickly regret spending that much money on it instead of just using paid APIs until proper hardware gets cheaper / models get smaller.
Yes, as someone who spent several thousand $ on a multi-GPU setup, the only reason to run local codegen inference right now is privacy or deep integration with the model itself.
It’s decidedly more cost efficient to use frontier model APIs. Frontier models trained to work with their tightly-coupled harnesses are worlds ahead of quantized models with generic harnesses.
Esp with RAM prices now spiking.
The point in this thread is that it would likely be too slow due to prompt processing. (M5 Ultra might fix this with the GPU's new neural accelerators.)
Because Apple has not adjusted their pricing yet for the new ram pricing reality. The moment they do, its not going to be a $10k system anymore but in the $15k+...
The amount of wafers going to AI is insane and will influence not just memory prices. Do not forget, the only reason why Apple is currently immunity to this, is because they tend to make long term contracts but the moment those expire ... then will push the costs down consumers.
What example tasks would you try?
The model output also IMO look significantly more beautiful than GLM-4.6; no doubt in part helped by ample distillation data from the closed-source models. Still, not complaining, I'd much prefer a cheap and open-source model vs. a more-expensive closed-source one.
It does feel like these models are only behind 6 months tho as many like to say and for some things its 100% reasonable to use it and for some others not so much.
Benchmarks aren't everything, but if you're going to contrast performance against a selection of top models, then pick the top models? I've seen a handful of companies do this, including big labs, where they conveniently leave out significant competitors, and it comes across as insecure and petty.
Claude has better tooling and UX. xAI isn't nearly as focused on the app and the ecosystem of tools around it and so on, so a lot of things end up more or less an afterthought, with nearly all the focus going toward the AI development.
$300/month is a lot, and it's not as fast as other models, so it should be easy to sell GLM as almost as good as the very expensive, slow, Grok Heavy, or so on.
GLM has 128k, grok 4 heavy 256k, etc.
Nitpicking aside, the fact that they've got an open model that is just a smidge less capable than the multibillion dollar state of the art models is fantastic. Should hopefully see GLM 4.7 showing up on the private hosting platforms before long. We're still a year or two from consumer gear starting to get enough memory and power to handle the big models. Prosumer mac rigs can get up there, quantized, but quantized performance is rickety at best, and at that point you look at the costs of self hosting vs private hosts vs $200/$300 a month (+ continual upgrades)
Frontier labs only have a few years left where they can continue to charge a pile for the flagship heavyweight models, I don't think most people will be willing to pay $300 for a 5 or 10% boost over what they can run locally.
I don’t know if the hallucinations extend to code, but it makes me unwilling to consider using it.
esafak•2h ago
CuriouslyC•2h ago
lanthissa•1h ago
hedgehog•1h ago
cmrdporcupine•1h ago
Imustaskforhelp•47m ago
bigyabai•1h ago
maxdo•52m ago
Imustaskforhelp•44m ago
People (here) are definitely comparing it to sonnet so if you take this stance of saving a few dollars, I am sure that you must be having the same opinion of using opus model and nobody should use sonnet too
Personally I am interested in open source models because they would be something which would have genuine value and competition after the bubble bursts
theshrike79•1h ago
Complete no-brainer to get it as a backup with Crush. I've been using it for read-only analysis and implementing already planned tasks with pretty good results. It has a slight habit of expanding scope without being asked. Sometimes it's a good thing, sometimes it does useless work or messes things up a bit.
maxdo•55m ago
sh3rl0ck•14m ago
I'd love to hear your insight though, because maybe I just configured things wrong haha