Bisheng vs RAGFlow
A side-by-side comparison of two self-hosted self-hosted ai options — licensing, setup difficulty, resource needs, and what each one replaces.
Not the right match-up?
Bisheng
Open LLM application platform for enterprise workflows
VS
RAGFlow
RAG engine with deep document understanding
| Feature | Bisheng | RAGFlow |
|---|---|---|
| Category | Self-Hosted AI | Self-Hosted AI |
| License | Apache-2.0 | Apache-2.0 |
| Language | Python | Go |
| Setup difficulty | Hard | Medium |
| Min. RAM | 4,096 MB | 8,192 MB |
| Deployment | docker | docker, kubernetes |
| GitHub stars | ★ 11,836 | ★ 87,057 |
| First released | 2023 | 2024 |
| Replaces | Dify | NotebookLM |
Why pick each one
Choose Bisheng if…
- Released under the Apache-2.0 license
- First-class Docker support for quick deployment
- Mature project with 11.8k GitHub stars
- Written in Python
Choose RAGFlow if…
- Released under the Apache-2.0 license
- First-class Docker support for quick deployment
- Kubernetes-ready with Helm charts available
- Mature project with 87.1k GitHub stars
Frequently asked questions
Is Bisheng or RAGFlow better?
RAGFlow is the stronger all-round pick: it has both the larger community and the simpler medium setup. Consider Bisheng if its specific feature set fits your needs better.
Are Bisheng and RAGFlow free and open-source?
Yes. Bisheng is licensed under Apache-2.0 and RAGFlow under Apache-2.0. Both can be self-hosted at no software cost.
Can I run Bisheng and RAGFlow with Docker?
Bisheng: yes. RAGFlow: yes.