Do you have a dumb question that you're kind of embarrassed to ask in the main thread? Is there something you're just not sure about?
This is your opportunity to ask questions. No question too simple or too silly.
Culture war topics are accepted, and proposals for a better intro post are appreciated.
Jump in the discussion.
No email address required.
Notes -
Ah. For Kimi K3 specifically, the weights haven't even been released yet, so it's basically just a (paid) preview mode. The mega-parameter models are also pretty much impossible to tune as an individual or small organization, and even the 200B-1T range is expensive. Model merges in this range mostly haven't worked, to the limited extent they worked cross-family to start with.
Most of the community ecosystems are focused more on the <50B range. Some of the lower visibility is just fragmentation, or the base models being good enough for a lot of purposes, or technical limitations (MoE models are much nicer to low-VRAM users, and also much harder to finetune), but there's just some awkward side effects of the highest-profile models being way outside of home enthusiast use. That said, Qwen3.6 got a massive amount of attention for that lower-range, and I'd expect any 3.8 <100B model gets similar focus.
And a lot of major providers have kinda settled on things as 'good enough'. NovelAI's highest-end model is a GLM-4.6 finetune at 355B param, which is great and all until you look at the release dates.
The movement toward tool use also makes things weird. There's no "here's an opencode project" sharing environment like there is Huggingface or CivitAI, for both obvious reasons (the LLMs can build it themselves... if you know enough to ask them the right questions) and technical ones (opencode has terrible project design and doesn't really distinguish templates from content as an intentional choice). But they do genuinely offer really strong ways to customize an LLM to your use case. So that's probably drawn a bit of the focus away from some of the finetunes.
More options
Context Copy link