GGUF hoards expose local LLM storage tax

Local AI's hidden bottleneck is not always GPU compute — it is the quiet sprawl of model files.

• –GGUF is the file format commonly used by llama.cpp, so large personal GGUF libraries are a good proxy for how serious local inference has become.
• –The thread matters because disk usage is now part of the cost model for self-hosted LLM work, alongside VRAM, RAM, and inference speed.
• –As developers keep multiple quants, model families, and fine-tunes around, storage management starts looking like real infrastructure work rather than hobbyist tinkering.
• –This is more community pulse than product news, but it is still useful for understanding where local LLM workflows create operational friction.