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InferenceReddit r/LocalLLaMA 13 d ago

Cutting LLM Token Costs with rtk, headroom, and caveman - savings measured on real workloads

The article evaluates the token cost savings of three tools—rtk, headroom, and caveman—when applied to real workloads from Claude Code sessions, totaling 614M tokens and $926 in baseline spend. The results showed modest savings: headroom achieved a 2.8% reduction ($25.61), rtk 0.5% ($4.94), and caveman 0.4% ($3.58), with a combined savings of 3.7% ($34.12). The limited impact on overall costs is attributed to the nature of the workloads, where high-compression techniques are less effective on plain text and source code, and the majority of the billing is derived from cache reads and outputs that these tools do not optimize.

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Cutting LLM Token Costs with rtk, headroom, and caveman - savings measured on real workloads — AI News Digest