TokenBeaver vs Headroom: compression layer or cost gateway?

Headroom is one of the most popular open-source answers to token waste, and it earned that: real engineering, honest benchmarks, impressive numbers. If you're choosing between it and TokenBeaver, here's a comparison that doesn't pretend either one is everything.

What Headroom is, and what it does well

Headroom is an open-source context-compression layer — a library, proxy, and MCP server that squeezes tool outputs, logs, files, and RAG chunks before they reach the model. Its README reports about 20% fewer tokens for coding agents and 60–95% for JSON-heavy payloads, with project benchmarks like a 92% cut on a code-search workload. Take those numbers at face value — the author, to their credit, invites you to A/B test on your own bill rather than trust the headline.

• Free and open source, with a genuinely clever per-content-type approach.
• Flexible: use it as a library inside your own stack, a proxy, or an MCP server.
• Especially strong on JSON-heavy and RAG-heavy pipelines.

Where the jobs differ

Headroom answers one question: how small can this context get? TokenBeaver answers a different one: what is my AI coding actually costing, and is it getting cheaper? Compression is one of the things a cost gateway does — it isn't the whole job.

• Proof, not just reduction. TokenBeaver meters every request on a localhost dashboard: cost per session, savings in dollars or plan runway — estimated on Free, verified on Pro, with a searchable Activity Log and CSV export. A compression library saves you tokens; it can't show your lead a ledger.
• Both personas. Compression percentages speak to API users. If you're on Claude Pro or Max, TokenBeaver frames the same work as runway — limit-hits avoided, window stretched — because a flat plan doesn't have a bill to shrink.
• Nothing lost, restorable. TokenBeaver slims requests without dropping what the model needs, and trimmed content can be restored on demand — so an aggressive squeeze never costs you a wrong answer and a re-ask.
• Zero integration work. One npm install, one command for Claude Code, one base URL for anything OpenAI-compatible. No code changes, no pipeline to redesign.

Pick honestly

Pick Headroom if you're building your own agent or RAG pipeline and want a compression layer you control in code — it's excellent at that, and it's free.

Pick TokenBeaver if you use Claude Code, Cursor, or another agent day-to-day and want the spend cut and proven — with a free-forever tier, and a Pro tier whose savings guarantee means a month that doesn't earn its keep is on us. Team-level governance is on our roadmap; today the product is built for your own seat. The TCO comparison covers the wider landscape.