n8n vs Langflow
The closest fight in this category. Both are visual, both self-host, both build AI agents by dragging boxes. The difference is what each was built around first: Langflow started from the model, n8n started from the integrations.
n8n vs Langflow: The Verdict
These two are genuinely close, and the choice comes down to what surrounds the AI. Langflow is AI-first: it began as a visual front end for LangChain, it is MIT-licensed with 154,086 GitHub stars, and it is now an IBM product. If you are prototyping prompt chains, RAG pipelines and agent behaviour, its canvas is built for exactly that and it exports to a Python-shaped artifact. n8n is automation-first: the AI Agent node sits inside a platform with 400+ integrations, cron and webhook triggers, encrypted credentials and execution history, because n8n was an automation tool that grew AI rather than an AI tool that grew scheduling. Pick Langflow if the AI logic is the product and the integrations are few. Pick n8n if the AI is one node in something that also has to talk to Slack, a CRM and a database on a schedule. One caution on cost comparisons: Langflow publishes no pricing at all - langflow.org/pricing returns 404, and IBM lists four editions with no figures - so anyone quoting you a Langflow Cloud price is guessing.
Last updated: 2026-09-02Quick Comparison
| Feature | Langflow | n8n |
|---|---|---|
| Built Around | AI and prompt chains first | Integrations and scheduling first |
| License | MIT (154,086 GitHub stars) | Sustainable Use License (199,633 stars) |
| Owner | IBM | n8n GmbH |
| Visual Builder | Yes | Yes |
| Non-AI Integrations | Limited - AI-focused components | 400+ built-in, 900+ community |
| Scheduling and Webhooks | Not the focus | Cron, webhook, form and chat triggers built in |
| Credential Storage | Basic | Encrypted at rest, per-credential |
| Execution History | Limited | Full history with per-node data |
| Desktop App | Yes - Langflow Desktop, macOS and Windows | No - it is a server app |
| Published Pricing | None - no pricing page exists | $7/mo self-hosted on InstaPods |
| Self-Hostable Free | Yes (MIT) | Yes (community edition) |
Where Langflow Runs Out
Trade-offs to weigh before committing.
Thin Outside the AI
Langflow is excellent at the model half and comparatively bare at everything else. If your flow needs to read a Google Sheet, post to Slack, update a CRM record and run every morning at 6, that is where n8n's 400+ nodes and trigger types do work Langflow expects you to do yourself.
No Published Pricing
langflow.org/pricing returns a 404 and IBM's product page lists four editions - Langflow OSS, IBM Elite Support for Langflow, IBM Langflow Desktop, and watsonx Orchestrate integration - with no prices on any of them. Self-hosting the OSS build is free, but budgeting for anything above it means talking to IBM.
Prototype-Shaped by Design
The canvas is built for iterating on prompts and chains. Running that as a scheduled production job, with retries, credential rotation and an audit trail of what ran when, is the part n8n treats as the main event.
Now an Enterprise Vendor Product
IBM ownership brings support options and enterprise runtime, and it also means the roadmap answers to enterprise buyers. That is a plus or a minus depending on which of those you are.
What n8n Adds Around the AI
What you get when you pick this stack.
A Price You Can Actually Read
n8n on InstaPods is $7/mo on the Build plan: 2 vCPU, 2 GB RAM, 25 GB SSD, HTTPS, daily backups and unmetered executions. Published, flat, no sales call.
The Integrations Are the Point
400+ built-in nodes plus 900+ community nodes, and an HTTP Request node for anything without one. In a real automation this is usually most of the work.
Triggers, Not Just Flows
Cron, webhook, form and chat triggers are first-class, so a workflow runs itself. That is the difference between a demo and a job.
Execution History When It Breaks
n8n stores per-node input and output for every run, so debugging a failure at 3am is reading a log rather than reproducing it.
Real Cost Comparison
A team running AI-assisted automations that also touch Slack, a database and a schedule.
- Langflow OSS: free (MIT)
- A server to host it: $5-20/mo, your call
- Non-AI integrations: build them yourself
- Scheduling and retries: build them yourself
- Support or enterprise runtime: price unpublished, contact IBM
- InstaPods Build plan: $7/mo (2 vCPU, 2 GB, 25 GB)
- n8n community edition: free, executions unmetered
- 400+ integrations: included
- Cron and webhook triggers: included
- Managed PostgreSQL on the same pod: included
Frequently Asked Questions
Is Langflow better than n8n?
For building and iterating on AI logic specifically - prompt chains, RAG pipelines, agent behaviour - Langflow's canvas is more focused and pleasant, because that is all it does. For anything where the AI is one step in a workflow that also has to move data between services on a schedule, n8n is the better fit by a wide margin. The AI half is close; the everything-else half is not.
Is Langflow free?
Langflow OSS is MIT-licensed and free to self-host, with full source access. Beyond that, no prices are published anywhere: langflow.org has no pricing page, and IBM's product page lists Langflow OSS, IBM Elite Support for Langflow, IBM Langflow Desktop and a watsonx Orchestrate integration without a figure against any of them.
Is Langflow owned by IBM?
IBM hosts the official Langflow product page at ibm.com/products/langflow and sells IBM Elite Support for Langflow and IBM Langflow Desktop as products. The project itself remains MIT-licensed and openly developed on GitHub.
Can n8n do everything Langflow does?
Close to it for the common cases. n8n's AI nodes are built on LangChain abstractions - the package is literally named @n8n/n8n-nodes-langchain - so agents, chat models, memory and vector stores are all there. Langflow exposes more of the chain internals and is nicer for pure experimentation. n8n wraps rather than exposes, and gives you the runtime around it.
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