Dify vs Langflow: Which Visual AI Agent Builder Should You Pick?

Dify vs Langflow comes down to who is building and what you’re shipping: Dify is the better pick for teams building knowledge-heavy RAG agents who want a managed cloud with defined plan tiers, while Langflow wins for developer-led teams who want a free, open-source visual builder with full Python control and MCP server support. Both are free to self-host, both target technical users, and neither is the right choice for a non-technical business user who wants an assistant out of the box. This comparison uses only vendor-published information — our hands-on testing notes for both tools are pending.

Dify vs Langflow at a glance

Sources: Dify pricing, Dify homepage, Langflow homepage.

How much does Dify cost compared to Langflow?

Langflow is cheaper to start with because it is fully open source: you can self-host it anywhere for free, and Langflow’s homepage also offers a free account on its cloud. Dify is free to self-host with Docker and has a free Sandbox cloud tier, but its paid cloud plans are metered.

Dify’s pricing page lists three cloud tiers:

1. Sandbox — free, for trying Dify.
2. Professional — 5,000 message credits per month, 3 members, 500 knowledge documents and 5 GB of knowledge storage.
3. Team — 10,000 message credits per month, 50 members, 1,000 documents and 20 GB of storage.

Dify’s pricing page does not publish flat dollar amounts for the paid tiers in our facts pack — it directs you to dify.ai/pricing — so treat costs as usage-based and check the page before budgeting. Annual billing saves 17% on cloud plans, per Dify. Enterprise deployments are custom-priced.

Illustrative scenario: a 5-person product team prototyping a support copilot could run both tools for free — Langflow’s open-source build on their own server, or Dify’s Sandbox — then move to Dify Professional when they need 5,000 message credits a month and shared knowledge documents. The cost question only really bites on Dify’s cloud; self-hosting either tool is free.

Which is easier to self-host, Dify or Langflow?

Both self-host well, but they differ in licensing and packaging. Dify is source-available and self-hosts with Docker, with enterprise deployments and support available for larger rollouts. Langflow is open source and can be self-hosted anywhere, per its homepage.

If your company needs a VPC or on-prem deployment with a vendor behind it, Dify’s Enterprise tier — which adds multiple workspaces and scalable deployment, per Dify’s site — is the more structured path. If your team just wants to run the software on your own infrastructure with no vendor conversation, Langflow’s open-source model is the simpler one. Both tools appear in our best self-hosted AI agent builders guide and the open-source and self-hosted category.

Which is better for RAG and knowledge-base agents?

Dify is the more complete out-of-the-box option for RAG. Its platform combines model and tool support, knowledge bases, triggers and workflows in one workspace, and its cloud plans scale knowledge capacity explicitly — 500 documents and 5 GB on Professional, 1,000 documents and 20 GB on Team, per Dify’s pricing page. Paid plans also list no Dify API rate limit.

Langflow supports all major LLMs and vector databases and ships hundreds of pre-built flows and components, per its homepage — so it is strong for RAG prototypes that will grow into production. The difference is assembly: Dify hands you the knowledge-base plumbing as a managed feature, while Langflow gives you the components and lets you wire (and customize) them yourself.

Illustrative scenario: a 10-person consultancy building a client-facing Q&A agent over hundreds of PDFs would get there faster on Dify, because document limits and storage are baked into the plan. A two-developer startup prototyping a retrieval flow they intend to rewrite in code later would prefer Langflow.

Which is better for developers who want code-level control?

Langflow wins clearly here. Every Langflow component is Python under the hood, you can customize anything in Python, and agents can use all your components as tools, per Langflow’s homepage. Our directory verdict calls it the most developer-friendly “no-code” tool in the directory — a good bridge between no-code and code.

Langflow also builds both AI agents and MCP servers visually, which Dify’s published materials do not list as a feature. If your roadmap includes exposing your agents as MCP servers, that alone may settle the decision. Langflow 1.13 was the current release when we checked, and the same Langflow runs self-hosted or on its cloud.

Dify is still a technical product — it is aimed at developers and technical PMs — but its customization story centres on the platform rather than per-component Python editing.

Who should choose Dify?

Choose Dify if you match one of these profiles:

1. A team building RAG or knowledge-base agents who wants managed storage, document limits and no API rate limit on paid plans.
2. A company that needs VPC or self-hosted deployment with an enterprise support option.
3. A team migrating from Flowise — our directory describes Dify as a natural migration path for Flowise users, and Dify cites 159K+ GitHub stars on its site.

Dify is not for non-technical users who want an assistant out of the box. If that is you, a tool like Lindy or the picks in our best no-code AI agent builders for small businesses guide will fit better.

Who should choose Langflow?

Choose Langflow if you match one of these profiles:

1. A developer or technical team that wants visual flows without losing code-level control.
2. A team building RAG or agent prototypes that will grow into production systems.
3. Anyone who needs to build MCP servers visually, or wants a fully open-source tool with a free cloud account to start.

Langflow is not for non-technical business users either. If you are weighing other developer-leaning options, our Flowise alternatives guide covers the same territory.

Bottom line

Dify vs Langflow is not a close call once you know your team: pick Dify for managed, knowledge-heavy RAG agents with clear cloud tiers and an enterprise path, and pick Langflow for free, open-source building with Python control and MCP server support. Both are free to self-host, so the cheapest way to decide is to run each for a week on a real use case.

What to ask next

• Is Dify worth paying for, or should I just self-host it? (see our Dify profile)
• What are the best free AI agent builders right now? (see our best free AI agent builders guide)
• How does Langflow compare to Flowise and other open-source builders? (see our Flowise alternatives guide)