head to head · open source
headroom vs gepa
headroom has 79,076 GitHub stars, 6,180 forks, 643 open issues and last shipped yesterday. gepa has 7,329 stars, 611 forks, 154 open issues and last shipped yesterday. headroom leads on adoption by 979% (79,076 vs 7,329 stars). headroom is written in Python under Apache-2.0; gepa is written in Jupyter Notebook under MIT. headroom has attracted 8% as many forks as stars, gepa 8%. headroom was the more recently maintained of the two, and both are self-hostable with no licence fee.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| headroom | gepa | |
|---|---|---|
| GitHub stars | ★ 79K | ★ 7.3K |
| License | Apache-2.0 | MIT |
| Written in | Python | Jupyter Notebook |
| Last push | 2026-11-07 | 2026-11-07 |
| Forks | ⑂ 6.2K | ⑂ 611 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick headroom if
- You weight community size — 79K stars and counting
- You want the Apache-2.0 license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick gepa if
- You want the gepa feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Jupyter Notebook
- You evaluated both and gepa fits your workflow better
About headroom
Quickstart · Install · Proof · Agents · Docs · Discord · llms.txt AI agents / LLMs: read /llms.txt here, or fetch the live index · full docs blob . Headroom compresses everything your AI agent reads — tool outputs, logs, RAG chunks, files, and conversation history — before it reaches the LLM. Same answers, fraction of the tokens. Compression runs on your machine; no prompt or file content is sent anywhere to be compressed. 10,144 → 1,260 tokens. The same FATAL found. What it does Library — compress(messages) in Python or TypeScript, inline in any app. Proxy — headroom proxy port 8787 , zero code changes, any…
read the full headroom overview →
About gepa
Optimize any text parameter — prompts, code, agent architectures, configurations — using LLM based reflection and Pareto efficient evolutionary search. Website     Quick Start     Paper     Blog     Discord What is GEPA? GEPA (Genetic Pareto) is a framework for optimizing any system with textual parameters against any evaluation metric. Unlike RL or gradient based methods that collapse execution traces into a single scalar reward, GEPA uses LLMs to read full execution traces — error messages, profiling data, reasoning logs — to diagnose why a candidate failed and propose…
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Frequently asked questions
Is headroom or gepa more popular?
headroom has 79,076 GitHub stars and gepa has 7,329. headroom has the larger community by that measure.
Are headroom and gepa free?
Both are open source. headroom is licensed under Apache-2.0 and gepa under MIT. Neither carries a licence fee.
What is the difference between headroom and gepa?
headroom is written in Python and gepa in Jupyter Notebook. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, headroom or gepa?
Choose headroom if you want the larger community (79,076 stars) or its Apache-2.0 licence terms. Choose gepa if its feature set, stack or MIT licence fits better. Both are self-hostable.