head to head · open source

headroom vs promptfoo

headroom has 73,130 GitHub stars, 5,624 forks, 643 open issues and last shipped yesterday. promptfoo has 25,297 stars, 2,344 forks, 651 open issues and last shipped today. headroom leads on adoption by 189% (73,130 vs 25,297 stars). headroom is written in Python under Apache-2.0; promptfoo is written in TypeScript under MIT. headroom has attracted 8% as many forks as stars, promptfoo 9%. promptfoo was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (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.

headroom ★ 73K promptfoo ★ 25K category AI & Machine Learning

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Side by side

headroom promptfoo
GitHub stars ★ 73K ★ 25K
License Apache-2.0 MIT
Written in Python TypeScript
Last push 2026-09-19 2026-09-20
Forks ⑂ 5.6K ⑂ 2.3K
Self-hosting Yes Yes
Data ownership Your server Your server

pick headroom if

  • You weight community size — 73K 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

full headroom profile →

pick promptfoo if

  • You want the promptfoo feature set and don't need the biggest community
  • You prefer the MIT license terms
  • Your stack matches TypeScript
  • You evaluated both and promptfoo fits your workflow better

full promptfoo profile →

About headroom

Headroom is an Apache 2.0 Python library, local proxy, agent wrapper and MCP server that compresses tool outputs, logs, files, RAG chunks and conversation history before they reach an LLM, and it is built for developers running AI coding agents or LLM applications who want to cut token usage without changing the answers they get.

read the full headroom overview →

About promptfoo

Promptfoo is an open source command line tool and TypeScript library for evaluating and red teaming large language model applications, aimed at developers, AI engineers, and security teams who need measurable evidence that a prompt, agent, or retrieval augmented generation pipeline behaves correctly and safely before it reaches users.

read the full promptfoo overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 247K Ollama ★ 181K Dify ★ 157K Open WebUI ★ 153K langchain ★ 147K

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openclaw vs dify openclaw vs multica openclaw vs langgraph n8n vs dify dify vs langflow dify vs open-webui dify vs langchain dify vs ponytail openclaw vs hermes-agent openclaw vs opencode openclaw vs n8n openclaw vs open-webui openclaw vs comfyui openclaw vs odysseus openclaw vs lobechat openclaw vs anythingllm openclaw vs ollama ollama vs llama-cpp ollama vs vllm ollama vs odysseus ollama vs gpt4all ollama vs llama-index ollama vs localai open-webui vs gpt4all

More AI Development Platforms projects

Compare either of these against the rest of the AI Development Platforms field.

headroom vs Dify headroom vs langchain headroom vs ponytail headroom vs generative-ai-for-beginners headroom vs graphify headroom vs claude-mem headroom vs ragflow headroom vs PaddleOCR headroom vs Agent-Reach headroom vs Mem0 headroom vs daily_stock_analysis headroom vs LiteLLM

Frequently asked questions

Is headroom or promptfoo more popular?

headroom has 73,130 GitHub stars and promptfoo has 25,297. headroom has the larger community by that measure.

Are headroom and promptfoo free?

Both are open source. headroom is licensed under Apache-2.0 and promptfoo under MIT. Neither carries a licence fee.

What is the difference between headroom and promptfoo?

headroom is written in Python and promptfoo 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 promptfoo?

Choose headroom if you want the larger community (73,130 stars) or its Apache-2.0 licence terms. Choose promptfoo if its feature set, stack or MIT licence fits better. Both are self-hostable.