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Dify vs n8n: Which Fits Your AI Workflow?

2026-11-15

Dify is an open-source platform for building LLM apps, and n8n is a fair-code workflow automation platform. Pick Dify when the product is the LLM app itself: prompts, retrieval, an agent, and an API in front of it. Pick n8n when events and connectors drive the work and the AI step is one stage in a longer process. If you would rather not build either, POLYROB is the third option: a self-hosted agent that is already built, and its autonomous runs stop at 150 steps and $2.00 by default (docs/[email protected]).

This page compares the two on what their own repositories say. Every fact about Dify and n8n was read on 2026-11-15 from a README or a license file, and each one links to its source. POLYROB gets its own section near the end, including where it loses.

How do Dify and n8n differ?

Sources: the Dify README and the n8n README, both fetched 2026-11-15.

What is the main difference between Dify and n8n?

Dify starts from the LLM application. n8n starts from the workflow.

The Dify README lists seven core features: a workflow canvas, model support across dozens of inference providers, a prompt IDE for comparing model performance, a RAG pipeline “from document ingestion to retrieval”, an agent, LLMOps monitoring, and Backend-as-a-Service. On the last one it says “All of Dify’s offerings come with corresponding APIs”, so an app you build in Dify is meant to be called from your own code. Its agent feature is described as autonomous agents “with a sandbox of their own” that run commands, install software and handle files, and that can use skills, Dify Marketplace tools, MCP servers or your own APIs.

The n8n README leads with automation: a canvas, custom code where you need it, and “multi-step AI workflows with logic, tool use, human approvals, and full observability”. An agent is one kind of step inside a larger flow that a webhook, a schedule or a new row can start.

In practice the same task looks different in each. “Let staff ask questions over our PDF handbook and expose that as an API” is a Dify-shaped job. “When a form is submitted, enrich the lead, ask a model to classify it and post to the sales channel” is an n8n-shaped job.

When should you choose Dify?

Choose Dify if these describe your project:

• You are building an LLM application and want retrieval, prompt testing and monitoring in one workspace.
• You want every app you build to come with an API for your own product.
• You need model choice. The README names GPT, Mistral, Llama3 and any OpenAI API-compatible model.
• You want a self-hosted install that starts from a single Docker Compose stack. The README gives the minimum as 2 CPU cores and 4 GiB of RAM.
• You need an enterprise edition with SSO, RBAC and support SLAs. The README points to Dify Enterprise for that.

Read the license before you build a service on it. The Dify LICENSE file says Dify “may be utilized commercially, including as a backend service for other applications or as an application development platform for enterprises”, and then adds two conditions under which a commercial license must be obtained:

• Multi-tenant service: “Unless explicitly authorized by Dify in writing, you may not use the Dify source code to operate a multi-tenant environment.” The file defines one tenant as one workspace.
• Logo and copyright: when using Dify’s frontend, “you may not remove or modify the LOGO or copyright information in the Dify console or applications.”

The file also says contributors agree that “the producer can adjust the open-source agreement to be more strict or relaxed as deemed necessary.” We are quoting the file, not giving legal advice. Dify’s own README describes the project as open source.

When should you choose n8n?

Choose n8n if these describe your project:

• The work is event-driven and the AI step is one stage of a longer process.
• Connectors matter more than custom agent logic: the README counts 1500+ integrations.
• People who do not write code need to read and change the flow, and you also want to drop into JavaScript or Python when the canvas runs out.
• You want a hosted option next to self-hosting. The README links the cloud login beside the Docker instructions.

Read its license too. The n8n LICENSE file says you may use or modify the software “only for your own internal business purposes or for non-commercial or personal use”, and that you may distribute it only “free of charge for non-commercial purposes.” Files with .ee. in the name need an n8n Enterprise License. That suits internal automation. If you plan to ship it inside a product for other people, ask n8n about your case.

How do the Dify and n8n licenses compare?

Sources: the Dify LICENSE and the n8n LICENSE.md, fetched 2026-11-15. Neither is a legal reading.

Can you use Dify and n8n together?

Nothing in either README stops you. Dify gives each app an API, and n8n lets a workflow run JavaScript, Python and npm packages, so an n8n flow can call a Dify app as one of its steps. n8n handles the triggers and the connectors around it, while Dify holds the retrieval and the prompts. The cost is two systems to learn, update and secure, and two licenses to read.

Where does POLYROB fit between Dify and n8n?

POLYROB is neither a canvas nor an app builder. It is the agent. You install it, describe a goal or a schedule in plain language, and it plans the steps, uses tools and reports back from a terminal, a web console or a chat app ([email protected]). It is MIT licensed ([email protected]), and its README says it is “Self-hosted, not a SaaS”.

curl -fsSL https://polyrob.dev/install.sh | bash
polyrob doctor

A recurring job is one line, from docs/guide/[email protected]:

/job new "every day 09:00" Summarise the inbox and post the three items that need me

What you get without building it, with the file behind each point:

• No flow-building tool underneath. The dependency list in [email protected] names neither Dify nor n8n.
• Scheduled jobs, plus goals that run in the background once you switch the dispatcher on with polyrob autonomy on (docs/[email protected]).
• A cap on every autonomous run: 150 steps (AUTONOMOUS_MAX_STEPS) and $2.0 (AUTONOMOUS_RUN_BUDGET_USD) by default (docs/[email protected]). The budget check fails open on a probe error, so treat it as a guard rail.
• Eight chat surfaces: Telegram, email, WhatsApp, Discord, Slack, Signal, Feishu / Lark and DingTalk ([email protected]).
• A REST API with SSE and an OpenAI-compatible /v1 endpoint, which is how you put it behind your own code ([email protected]).
• An MCP client, so it can use tools from any MCP server ([email protected]). The MCP client guide shows the setup.

Pick it if the job is “keep working on this and ask me before high-impact steps” and you would rather configure an agent than draw one. The self-hosted AI agent guide walks through a full install, and the open source AI agent guide covers the license side.

Where does POLYROB lose to Dify and n8n?

Plainly:

• No visual builder. The web console has five destinations: Chat, Inbox, Work, Money and Agent (docs/guide/[email protected]). None of them is a flow or app editor.
• Integrations. n8n lists 1500+. POLYROB ships tools for the web, files, code, a shell, mail and MCP ([email protected]). Anything else comes through MCP or a skill you write.
• Hosting. The POLYROB README says there is no hosted version, while Dify and n8n both run a cloud.
• Community size. POLYROB is the newer project, with a smaller community (docs/[email protected]).
• Non-developer reach. Both competitors are built for people who work on a canvas. POLYROB is configured in text.
• Migration. Nothing converts a Dify app or an n8n flow, so moving one means describing the job to the agent again.

How do you decide?

If none fits, see our lists of n8n alternatives, the Langflow vs n8n comparison, or n8n vs LangChain.

Frequently asked questions

Why is n8n called n8n?

The n8n README says the name means “nodemation”, pronounced n-eight-n. The founder, Jan Oberhauser, explains that “node-” refers to the node view and Node.js, and “-mation” to automation, and that the long name was shortened to n8n for the command line.

How much does n8n cost per month?

We did not read n8n’s price list for this page, so we give no numbers. The README says you can self-host it or use n8n Cloud. Check the current plans on n8n’s own pricing page before you decide, and read the license limits above if you self-host for a product.

Who is the competitor for n8n?

It depends on the job. Dify is the closest match when the work is an LLM app. Langflow is a visual builder for agents and flows. A ready-made agent such as POLYROB fits when you want something that works toward a goal without a flow to draw. For a longer list, see n8n alternatives.

Is Dify open source?

Dify’s README describes it as an open-source LLM app platform. Its LICENSE file is a modified version of the Apache License 2.0 with the two added conditions quoted above, so read them against your plans.

Sources

Fetched 2026-11-15: the Dify README, the Dify LICENSE, the n8n README and the n8n LICENSE file. POLYROB facts are from the public repository at tag v1.7.10. Projects change quickly: check each link before you decide.

To try an agent that is already built, read how to install POLYROB.

POLYROB is an open-source AI agent you run and own. Install it or read the docs.