head to head · open source
headroom vs contextgem
headroom has 78,845 GitHub stars, 6,162 forks, 643 open issues and last shipped yesterday. contextgem has 2,064 stars, 190 forks, 0 open issues and last shipped 8 days ago. headroom leads on adoption by 3,720% (78,845 vs 2,064 stars). headroom is written in Python under Apache-2.0; contextgem is written in Python under Apache-2.0. headroom has attracted 8% as many forks as stars, contextgem 9%. headroom was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 2 topic tags (ai, llm), so they are genuine substitutes rather than adjacent tools.
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 | contextgem | |
|---|---|---|
| GitHub stars | ★ 79K | ★ 2.1K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-11-04 | 2026-10-28 |
| Forks | ⑂ 6.2K | ⑂ 190 |
| 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 contextgem if
- You want the contextgem feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Python
- You evaluated both and contextgem 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 contextgem
ContextGem: Effortless LLM extraction from documents ContextGem is a free, open source LLM framework that makes it radically easier to extract structured data and insights from documents — with minimal code. 💎 Why ContextGem? Reliable structured extraction from documents typically involves writing extraction prompts, designing validation models, mapping outputs back to source references, orchestrating multi step pipelines, and tracking usage across LLMs. ContextGem handles all of this through powerful abstractions — you describe what to extract in natural language, and the framework handles how . The result…
read the full contextgem overview →
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Frequently asked questions
Is headroom or contextgem more popular?
headroom has 78,845 GitHub stars and contextgem has 2,064. headroom has the larger community by that measure.
Are headroom and contextgem free?
Both are open source. headroom is licensed under Apache-2.0 and contextgem under Apache-2.0. Neither carries a licence fee.
What is the difference between headroom and contextgem?
headroom is written in Python and contextgem in Python. 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 contextgem?
Choose headroom if you want the larger community (78,845 stars) or its Apache-2.0 licence terms. Choose contextgem if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.