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This paper presents the first systematic study of zero-knowledge-friendly quantization for LLMs, formalizing the concept and evaluating nine models (including Qwen2.5-14B and Qwen3-30B-A3B) across weight, activation, and nonlinear lookup table precision. It finds that activation precision and RMSNorm inverse-square-root lookups dominate ZK proving costs and that conventional low-bit quantization heuristics do not translate to proportional proving savings.