Dify vs 
Langflow
Dify vs Langflow compared for 2026 — features, license, ease of use, performance and which one to choose. Build and operate AI apps visually vs Visual builder for agents and RAG.
Updated regularly · curated by olud.ai
Dify vs Langflow at a glance
| Spec | Dify | Langflow |
|---|---|---|
| Category | Low-code AI builder | Low-code AI builder |
| Type | LLMOps platform | Visual LLM builder |
| License | Apache-2.0 | MIT |
| Runs locally | Self-hosted | Self-hosted |
| Primary language | Python / TS | Python |
| Ease of use | Beginner | Beginner |
| Best for | teams shipping production AI apps with less code | Python teams who want a visual flow canvas |
| GitHub stars | 149.7k | 152.2k |
Feature comparison
| Feature | Dify | Langflow |
|---|---|---|
| Visual builder | ✓ | ✓ |
| Document RAG | ✓ | ✓ |
| Self-hostable | ✓ | ✓ |
| API export | ✓ | ✓ |
| Many integrations | ✓ | ✓ |
| Agents | ✓ | ✓ |
How Dify and Langflow score
| Criterion | Dify | Langflow |
|---|---|---|
| Popularity | 5.0 | 5.0 |
| Maintenance | 5.0 | 5.0 |
| Ease of use | 5.0 | 5.0 |
| Privacy | 4.5 | 4.5 |
| License freedom | 5.0 | 5.0 |
Scores are computed automatically from public signals — GitHub stars (popularity), recent commit activity (maintenance), license type (freedom), local-first design (privacy) and onboarding complexity (ease of use). Indicative, not a verdict.
What each one is
Dify
Dify is an open-source LLMOps platform to visually build, deploy and operate AI applications and agents, with RAG, workflows and observability built in.
- Full LLMOps: build, deploy and monitor
- Visual workflows plus built-in RAG
- Production-oriented with observability
Langflow
Langflow is a visual, Python-based builder for agentic and RAG applications, with a node canvas and an API to deploy your flows.
- Python-native visual flow canvas
- Agent and RAG components out of the box
- Deploy flows as APIs
Key differences
Dify is lLMOps platform, while Langflow is visual LLM builder. Their licenses differ (Apache-2.0 vs MIT), which matters if you ship a commercial product. In short, Dify fits teams shipping production AI apps with less code, and Langflow fits Python teams who want a visual flow canvas.
Which should you choose?
Choose Dify for teams shipping production AI apps with less code. Choose Langflow for Python teams who want a visual flow canvas.
There is rarely one winner — many setups use both. The right pick depends on your hardware, your team's skills, and whether you value simplicity or control.
Frequently asked questions
Is Dify or Langflow easier to use?
Both sit at a similar level (Beginner). Your choice should come down to fit rather than difficulty.
Are Dify and Langflow free?
Dify is free and open source (Apache-2.0), and Langflow is free and open source (MIT). Neither charges for the core software.
Can I run Dify and Langflow locally?
Dify: self-hosted · Langflow: self-hosted. Both can be used without sending your data to a third-party cloud where their setup allows.
Dify vs Langflow — which should I pick in 2026?
Choose Dify for teams shipping production AI apps with less code. Choose Langflow for Python teams who want a visual flow canvas.
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