Dify vs Flowise vs Langflow
Flowise is the fastest way to prototype a RAG chatbot on a canvas. Langflow is the same idea for teams already committed to LangChain. Dify is the heaviest and the most complete — workspaces, datasets, published apps with APIs — and the only one of the three that feels like a platform rather than a builder.
At a glance
| Dify | Flowise | Langflow | |
|---|---|---|---|
| Shape | Platform with workspaces and datasets | Canvas for flows and agents | Canvas over LangChain components |
| Time to a first prototype | An afternoon | Under an hour | Under an hour |
| RAG ingestion | Configurable pipeline in the UI | Assembled from nodes | Assembled from components |
| Publishing | Apps with their own API keys | API and embeddable widget | API export |
| Licence | Apache-2.0 with conditions | Apache-2.0 | MIT |
| Memory needed | 8 GB and up | 4 GB | 4 GB |
| Hosted here from | $18.99/mo | $11.99/mo | $11.99/mo |
Prototype speed versus staying power
Flowise and Langflow win the first hour. Drag a loader, a splitter, an embedding model and a vector store onto a canvas, put an LLM node at the end, and there is a working RAG chatbot with an API and an embeddable widget. For proving an idea to someone who needs to see it, nothing here is faster.
Dify wins the sixth month. Datasets are managed rather than wired, prompts are versioned where non-developers can see them, apps are published with their own keys, and there is a notion of a workspace with members. The cost is a heavier stack and a steeper first day.
Licence conditions worth knowing before you build
Dify is Apache-2.0 with additional conditions: you may not run it as a multi-tenant service without permission, and the Dify branding must remain. Single-tenant deployments — one instance per customer — satisfy both, which is how every instance here is provisioned.
Flowise has no licence complication but does have a security one: versions before 3.0.6 carry a critical remote code execution advisory (CVE-2025-59528). An internet-facing Flowise on an older build is a genuine risk; we never deploy below the fixed release.
Langflow is MIT with nothing unusual attached.
When none of the three is the answer
If the job is “point it at our documents and let people ask questions”, a builder is overkill — AnythingLLM does that out of the box with citations and workspaces. If the source material is annual reports, scanned pages and complex tables, RAGFlow parses them properly instead of flattening everything to plain text.
Builders earn their keep when the logic is non-trivial: branching, tool calls, several data sources, conditional routing.
The verdict
Prove the idea on Flowise. Run it long-term on Dify if it becomes something the business depends on. Pick Langflow if your team already writes LangChain and wants a visual layer over the same components. And check whether AnythingLLM already does what you are about to build.
Mentioned on this page
Dify
A visual studio for building LLM apps, agents and RAG pipelines.
from $18.99/moDetails →
Flowise
Drag-and-drop LLM flows, agents and chatbots you can embed anywhere.
from $11.99/moDetails →
Langflow
A visual builder for LangChain flows and multi-agent systems.
from $11.99/moDetails →
AnythingLLM
A private document workspace — drop files in, ask questions, get cited answers.
from $18.99/moDetails →Questions
Can I export a Flowise flow into Dify?
Is Dify free to use commercially?
Which needs the most memory?
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