I regret that the projection models ended up separate, and I too would have preferred for them to be in a single file. I'm not entirely sure why that ended up happening, but it very much runs counter to the single-file ethos I had in mind when I designed GGUF.

Hoping that someone will shepherd the cause of merging the two; I think I'm too out of the loop to do it this time around :-)

GGML & GGUF have been extremely important to the open-source ML/AI space. Projects like llama.cpp, whisper.cpp, and stable-diffusion.cpp tend to just work perfectly, across a whole bunch of different platforms and hardware backends.

> The really neat thing about GGUF is that it's just one file. Compare this to a typical safetensors repo on huggingface, where there's a pile of necessary JSON files scattered around [...]

Funny, to me AI models have "always" been single files, as that's what has been the norm in the local image gen business. Safetensors files allow stuffing all kinds of stuff inside them too, no GGUF needed for that. Though given that the text encoders of modern models are multi-gigabyte language models themselves, nobody includes redundant copies of those in every checkpoint.

IMO the biggest thing still missing is an actual way to define the model architecture outside of being hard coded into the current build. It doesn't need to be a 1:1 performance parity with the fully supported models. Having proper, vendor validated support for day 1 is what is the difference between people thinking a model is amazing vs horrible. See recent Gemma vs Qwen releases.

Not sure what the solution is, other than writing a DSL to describe the model graphs which you then embed in the GGUF. The other fallback is to just read the PyTorch modules from the official model releases and convert that to GGML ops somehow.

> not to be confused with the somewhat baffling llama_chat_apply_template exposed in the libllama API, which hardcodes a handful of chat formats directly in C++

As someone who is tinkering with a desktop-based inference app in FLTK[0], i wish this used the actual Jinja2 template parser llama.cpp uses (or there was another C function that did that since AFAICT for "proper" parsing you need to be able to pass a bunch of data to the template so it knows if you, e.g., do tool calling). Currently i'm using this adhocky function, but i guess i'll either write a Jinja2 interpreter or copy/paste the one from llama.cpp's code (depending on how i feel at the time :-P).

But yeah, GGUF's "all-in-one" approach is very convenient. And i agree that it feels odd to have the projection models as separate files - i remember when i first download a vision-capable model, i just grabbed whatever GGUF looked appropriate, then llama.cpp told me it couldn't do model and took me a bit to realize that i had to download an extra file. Literally my thought once i did was "wasn't GGUF supposed to contain everything?" :-P

[0] https://i.imgur.com/GiTBE1j.png

> <|turn>user Hi there!<turn|><|turn>model Hi there, how can I help you today <turn|>

Good lord, they managed to invent a format that is even less readable than XML.

Nice, I recently pulled down TheBloke 7B mistral to try out I have a 4070.

>Published May 18, 2026

hmmm...