Reddit user asks about hardware sizing rationale for LLM model size niches

A Reddit user in the r/LocalLLaMA community seeks an explanation for the specific parameter count ranges of popular local Large Language Models, such as ~30B, ~70B, ~120B, and ~230B. The author notes observed gaps in model sizes and asks whether these niches are determined by server-level hardware memory constraints or consumer GPU VRAM limits at specific quantization levels like 8-bit or Q4. The post requests clarification on how hardware setups influence the intended sizing of these distinct model categories.