Comparison · Updated 2026-10-19
Headroom vs Caveman
Headroom and Caveman both cut coding agent tokens but start from different sides. Headroom is a local proxy and library that compresses inputs by content type. Caveman began as a skill for terse replies and now adds local input reducers. If you want a hosted, question-aware option instead, SuperCompress keeps only the original lines answering your question.
What is Headroom?
Headroom is an Apache-2.0 project, installed with pip install "headroom-ai[all]", that sits between your app or agent and the provider. It ships a Python and TypeScript library, a local proxy, an agent wrapper and an MCP server. A router detects each block's type (JSON, logs, diffs, HTML, code, text) and sends it to a matching compressor, and it can cache originals locally for retrieval. Sources: GitHub, architecture docs.
What is Caveman?
Caveman is an Apache-2.0 project that started as a Claude Code skill making the agent answer in short sentences while leaving code exact. Its CLI (npx @caveman-ai/cli@latest) now bundles several parts, including local shrinking of logs, JSON and test output and compressed web pages, and runs on your machine with your own logins. Its docs state that the reply skill itself does not compress input. Sources: GitHub, Caveman docs.
How do Headroom and Caveman differ?
| Headroom | Caveman | SuperCompress | |
|---|---|---|---|
| Starting point | Input compression | Shorter replies | Input compression |
| How it picks what to keep | Content-type compressors | Format-specific local reducers | Hosted model scores lines against the question |
| Where it runs | Locally | Locally | Hosted API |
| Changes agent's voice | No | Yes, by design | No |
| Install | pip package | npx CLI or skill alone | npm install -g supercompress-proxy, supercompress setup |
Which should you pick?
- Headroom if you need local, in-process compression inside a Python or TypeScript app.
- Caveman if you like terse replies and want a local bundle of reducers.
- SuperCompress if your problem is huge outputs where a few lines matter and you want them kept verbatim without running a local pipeline.
How do you test them fairly?
Both projects publish their own figures. Run your real tasks with each, confirm they still succeed, and compare spend per finished task. More options in context compression tools compared.
npm install -g supercompress-proxy && supercompress setupFrequently asked questions
Is Headroom or Caveman better?
Neither is better in general. Headroom focuses on local input compression by content type; Caveman focuses on terse replies with added local reducers.
Are Headroom and Caveman free?
Both are Apache-2.0 projects on GitHub. Caveman also offers a separate hosted product for teams.
Can I use Headroom and Caveman together?
Caveman's reply skill acts on output, so it can sit beside an input compressor. Running two input compressors on the same content needs testing.
What is a hosted alternative to Headroom and Caveman?
SuperCompress is hosted: the Neural Keep model on the SuperCompress API keeps the original lines that answer your question.