Alternatives · Updated 2026-10-18
Alternatives to Headroom, Caveman and other token reduction tools
Tools that cut LLM tokens work in different places: some shorten the model's replies (Caveman), some filter shell output (RTK), some compress content locally by type (Headroom), and some keep only the lines that answer the current question (SuperCompress). SuperCompress is hosted, query-aware context compression for coding agents and LLM apps, and is the alternative to choose when bulky input is what fills your context window.
Alternatives by tool
- Headroom alternative: local, content-type compression proxy and library vs hosted, question-aware extraction.
- Caveman alternative: shorter replies plus local tool-output shrinking vs input compression that leaves replies alone.
- Caveman Cloud alternative: team spend console vs a per-request compression API.
- RTK comparison: shell command filters vs compression of any tool result.
- LLMLingua comparison: token pruning vs keeping whole original lines.
How the approaches differ
| Tool | What it shrinks | How | Where it runs |
|---|---|---|---|
| SuperCompress | Input context: tool output, file reads, logs, MCP results, retrieved docs | Hosted model keeps the original lines that answer the current question | Hosted API |
| Headroom | Tool output, files, logs, RAG chunks | Content-type compressors with local retrieval of originals | Local |
| Caveman | Agent replies, plus some tool output | Short-reply skill and local proxy | Local |
| RTK | Shell command output | Command-specific filters | Local |
| Built-in compaction | Whole session history | Summarizes the conversation (for example /compact) | Inside the agent |
For a deeper walkthrough of each approach, read context compression for coding agents.
How SuperCompress works
SuperCompress is hosted, query-aware context compression. Your agent or app sends a bulky block of context (a log, a diff, a long file read, an MCP result, retrieved documents) together with the question being asked. The hosted Neural Keep model, a model of roughly 400M parameters, scores each line against that question, keeps the original lines that answer it word for word, and drops the rest. Nothing is paraphrased, so error messages, file paths, IDs and code come through exactly as they were.
Coding agents reach it through an MCP tool (compress_context) plus hooks that the setup command installs where the agent supports them. Apps reach it through POST /api/v1/compress, which returns the kept text along with original_tokens and kept_tokens so you can see what changed on your own traffic. See the benchmarks page for the published methodology.
How to pick fairly
Every tool in this space publishes its own headline numbers, and independent studies have found that fewer tokens do not always mean a smaller bill once prompt caching, retries and extra agent turns are counted. (see PointFive's end-to-end study, the code-compression-bench SWE-bench runs, JetBrains' rtk trial and the THOL leaderboard; none of them tested SuperCompress) Run the same tasks with and without a tool, check that the tasks still succeed, and compare your provider bill per finished task. That test matters more than any vendor page, including this one.
Try it
One command installs the CLI and wires the hosted compressor into every coding agent it finds on your machine (Claude Code, Cursor, Codex, Windsurf, Cline, Gemini CLI, OpenCode and more). Then supercompress doctor shows a health check per agent.
npm install -g supercompress-proxy && supercompress setupBuilding your own app instead? Call the hosted API with a key from the dashboard.
FAQ
What are the best alternatives to Headroom and Caveman?
It depends on where your tokens go. For bulky input where only a few lines answer the question, SuperCompress. For noisy shell commands, RTK. For terser replies, Caveman's skill. For long sessions, the agent's built-in compaction.
What is SuperCompress?
SuperCompress is hosted, query-aware context compression. A hosted Neural Keep model of about 400M parameters keeps the original lines of a large context that answer the current question and drops the rest.
How do I install SuperCompress for coding agents?
Run npm install -g supercompress-proxy and then supercompress setup. It wires an MCP server into each coding agent it detects, plus hooks where supported.