head to head · open source
Dify vs loop-engineering
Dify has 160,251 GitHub stars, 25,336 forks, 1,067 open issues and last shipped yesterday. loop-engineering has 11,683 stars, 1,575 forks, 9 open issues and last shipped yesterday. Dify leads on adoption by 1,272% (160,251 vs 11,683 stars). Dify is written in Python under a custom or non-standard licence; loop-engineering is written in TypeScript under MIT. Dify has attracted 16% as many forks as stars, loop-engineering 13%. Dify was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 3 topic tags (agentic-ai, automation, claude), 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.
← all 20902 open source comparisons
Side by side
| Dify | loop-engineering | |
|---|---|---|
| GitHub stars | ★ 160K | ★ 12K |
| License | Custom / other | MIT |
| Written in | Python | TypeScript |
| Last push | 2026-11-02 | 2026-11-02 |
| Forks | ⑂ 25K | ⑂ 1.6K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick Dify if
- You weight community size — 160K stars and counting
- You want the Custom / other license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick loop-engineering if
- You want the loop-engineering feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches TypeScript
- You evaluated both and loop-engineering fits your workflow better
About Dify
Dify Cloud · Self hosting · Documentation · Dify edition overview Dify is an open source LLM app development platform. Its intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features (including Opik, Langfuse, and Arize Phoenix) and more, letting you quickly go from prototype to production. Here's a list of the core features: Quick start Before installing Dify, make sure your machine meets the following minimum system requirements: CPU = 2 Core RAM = 4 GiB The easiest way to start the Dify server is through Docker Compose. Before running Dify with the…
About loop-engineering
Loop Engineering Stop prompting. Design the loop. Get a score. Start in 5 minutes · Quickstart · What do you want to do? · Refactor path · 中文 · Pattern picker tool defaults to claude if you omit it. Swap for grok , codex , or opencode . Week one is report only . You design a system that discovers work, hands it to agents, verifies results, and persists state — instead of typing the next prompt yourself. New here? Quickstart · Refactor a project · Thin GitHub Action loop (no STATE.md required) What do you want to do? This is a pattern library for operating agents around a codebase . It is not a “rewrite the…
read the full loop-engineering overview →
More in AI & Machine Learning
Related comparisons
More AI Development Platforms projects
Compare either of these against the rest of the AI Development Platforms field.
Frequently asked questions
Is Dify or loop-engineering more popular?
Dify has 160,251 GitHub stars and loop-engineering has 11,683. Dify has the larger community by that measure.
Are Dify and loop-engineering free?
Both are open source. Dify has no licence declared in this registry, and loop-engineering is licensed under MIT. Both are free to self-host.
What is the difference between Dify and loop-engineering?
Dify is written in Python and loop-engineering 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, Dify or loop-engineering?
Choose Dify if you want the larger community (160,251 stars) or its Custom / other licence terms. Choose loop-engineering if its feature set, stack or MIT licence fits better. Both are self-hostable.