Cut LLM Token Costs Up to 90% with Context Compression (2026)

#llm #context #compression #cut

Originally published on rohitraj.tech

Headroom hit #1 on GitHub Trending on June 4, 2026 with a tool that compresses tool outputs, logs, and RAG chunks before they reach the model — cutting input tokens up to 92%. Here's how LLM context compression actually works, how Headroom stacks up against LLMLingua, prompt caching, and RAG reranking, when it quietly breaks, and how I'd wire it into a production MVP without losing accuracy.

Read the full version with code samples, diagrams, and architecture details: Cut LLM Token Costs Up to 90% with Context Compression (2026)

More engineering notes: rohitraj.tech/en/notes