Most LLM cost comes from input tokens, the long documents, codebases, or conversation histories you send as context. There are several prompt compression algorithms available, but nobody tells you which one actually works best for your specific workload, or how much quality you are trading for the savings. Prompt Compression Benchmarker (PCB) answers both questions. It benchmarks every major prompt compression algorithm against your actual data, shows you exactly how much quality each one drops, projects the real dollar savings at your call volume, and then gives you a one-line wrapper to deploy the winner as a drop-in replacement around your Anthropic or OpenAI client. What It Does PCB answers two questions: Which compression algorithm preserves the most quality at a given token budget? Benchmark mode runs all compressors against your data and scores each one with task-specific quality metrics and an optional LLM-as-judge. How much money does that save at your actual call volume?…