head to head · open source
headroom vs LLM Gateway
headroom has 78,773 GitHub stars, 6,155 forks, 643 open issues and last shipped yesterday. LLM Gateway has 1,724 stars, 200 forks, 77 open issues and last shipped yesterday. headroom leads on adoption by 4,469% (78,773 vs 1,724 stars). headroom is written in Python under Apache-2.0; LLM Gateway is written in TypeScript under a custom or non-standard licence. headroom has attracted 8% as many forks as stars, LLM Gateway 12%. headroom was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 3 topic tags (ai, anthropic, 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 | LLM Gateway | |
|---|---|---|
| GitHub stars | ★ 79K | ★ 1.7K |
| License | Apache-2.0 | Custom / other |
| Written in | Python | TypeScript |
| Last push | 2026-11-04 | 2026-11-04 |
| Forks | ⑂ 6.2K | ⑂ 200 |
| 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 LLM Gateway if
- You want the LLM Gateway feature set and don't need the biggest community
- You prefer the Custom / other license terms
- Your stack matches TypeScript
- You evaluated both and LLM Gateway 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 LLM Gateway
LLM Gateway LLM Gateway is an open source API gateway for Large Language Models (LLMs). It acts as a middleware between your applications and various LLM providers, allowing you to: Route requests to multiple LLM providers (OpenAI, Anthropic, Google Vertex AI, and others) Manage API keys for different providers in one place Track token usage and costs across all your LLM interactions Analyze performance metrics to optimize your LLM usage Features Unified API Interface : Compatible with the OpenAI API format for seamless migration Usage Analytics : Track requests, tokens used, response times, and costs Multi…
read the full LLM Gateway overview →
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Frequently asked questions
Is headroom or LLM Gateway more popular?
headroom has 78,773 GitHub stars and LLM Gateway has 1,724. headroom has the larger community by that measure.
Are headroom and LLM Gateway free?
Both are open source. headroom is licensed under Apache-2.0, and LLM Gateway has no licence declared in this registry. Both are free to self-host.
What is the difference between headroom and LLM Gateway?
headroom is written in Python and LLM Gateway in TypeScript. 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 LLM Gateway?
Choose headroom if you want the larger community (78,773 stars) or its Apache-2.0 licence terms. Choose LLM Gateway if its feature set, stack or Custom / other licence fits better. Both are self-hostable.