unsloth/Devstral-Small-2507-unsloth-bnb-4bit · Understanding bnb-4bit vs. GGUF for LLM Inference

Hello everyone,

I'm new to the world of LLMs and was hoping to get some advice from those with more experience.

I've noticed that for LLM inference, the bnb-4bit format seems to be a common recommendation. Is it generally preferred over other formats like GGUF?

From what I can gather, the main purpose of bnb-4bit is to reduce the model's memory footprint, but I've also observed that GGUF models tend to have significantly more downloads. This has left me a bit confused.

Could someone clarify the primary use case for bnb-4bit and why GGUF might be more popular in terms of download numbers?

Any insights you can share would be greatly appreciated as I'm still learning the ropes. Thank you in advance!