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Make vs n8n
A plain-English comparison to help you choose between them.
Pick Make for the polished hosted experience with deep visual logic and no infrastructure to run; pick n8n when self-hosting, code-level control and freedom from per-task economics matter more than polish. Make is the power tool you rent; n8n is the one you own.
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Side by side
- Summary
Make is visual automation with engineering sensibilities: scenarios built on a canvas where branching, loops, error handling and data transformation are first-class, connecting thousands of apps at credit-based pricing that undercuts the per-task platforms at volume.
AI has become native: agents live inside the scenario builder as reusable, shareable components, with their reasoning and tool calls visible step by step, and a real-time visual map keeps a growing automation estate comprehensible.
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It rewards builders who think in flows: more capable than the simplest platforms, more approachable than code, with credit billing that still compounds at serious scale.
- Best for
- Branching, loops and error handling built visually
- High-volume automation at credit-based pricing
- Reusable AI agents inside scenarios, reasoning visible
- Data transformation between connected apps
- A visual map of the whole automation estate
- Cost
- Freemium (Free tier + paid plans)
- Ease
- Openness
- Hosted service
- Data
- Per Make's Help Center, "effective august 27th, 2025, we're replacing operations with credits as our billing unit," with existing operations converting 1:1. Standard modules stay at 1 credit, but native AI modules consume credits variably: per one 2026 review, "A workflow with AI Agents can consume 43-50 credits per execution (Small model), versus the few credits of a classic workflow." Extra credits cost 25% more than in-plan (Help Center, updated 6 Nov 2025), for both manual and auto-purchase. The sticker price is not the bill; consider calling AI APIs directly via HTTP for cost control.
- Summary
n8n is the engineer's automation platform: open source and self-hostable, with execution-based pricing that keeps high-volume workflows economical, visual nodes that accept real code when logic demands it, and first-class support for AI and agentic flows.
Self-hosting is the headline: data residency, compliance and cost control all follow from running it on your own infrastructure, with a hosted option when that is not the point.
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It rewards technical users and punishes casual ones: the curve is steeper than the consumer platforms, and the operational effort is yours.
- Best for
- Self-hosted automation with data residency
- Execution-based pricing at high volume
- Visual flows with real code where needed
- AI and agentic workflows under your control
- Technical teams who want to own the platform
- Cost
- Freemium (Free tier + paid plans)
- Ease
- Openness
- Runs privately (self-hostable)
- Data
- Execution-based pricing (whole workflow = one execution) is usually cheaper than per-task, but AI Workflow Builder credits (50 Starter / 150 Pro) and any LLM API calls you wire in are metered separately, and Business overage is charged per block of extra executions. The sticker price is not the whole bill. Self-hosting shifts cost to your own infrastructure/maintenance.
Pricing
- Make
Free·from $9·from $16·from $29·Custom
Prices as of August 2026.
- Free
- Free
- Core
- from $9per monthbilled annually; $10.59 per month if billed monthly
- Pro
- from $16per monthbilled annually; $18.82 per month if billed monthly
- Teams
- from $29per monthbilled annually; $34.12 per month if billed monthly
- Enterprise
- Price on applicationno list price published
- n8n
$20·$50·$800·Custom
Prices as of August 2026.
- Starter
- $20per monthbilled annually
- Pro
- $50per monthbilled annually
- Business
- $800per monthbilled annually
- Enterprise
- Price on applicationno list price published
By area
Where each one pulls ahead, area by area.
| Area | Make | n8n |
|---|---|---|
| By job | ||
| AI agents & automation | Make is the reasonable choice when one person owns automation as part of their job and would rather see every scenario laid out than listed | n8n lets its visual nodes accept real code the moment the logic outgrows them, so a workflow never has to be rebuilt in a different tool when it gets hard |
| Founders & entrepreneurs | Make automates the onboarding with a branch per customer type and transforms the data between tools instead of anyone re-entering it | n8n automates the product's plumbing rather than only the office's, and scales those workflows with the company instead of replatforming once they matter |
| By task | ||
| Automation & agents | Make connects thousands of applications with real transformation between them, so the data arriving at the second app is already in the shape that app needs | n8n keeps the data on your own infrastructure and versions the workflows like the code they actually are, mixing visual nodes with real code wherever the logic demands it |
Common questions
Is self-hosting n8n actually hard?
For anyone comfortable with Docker and a small server, no: a working instance takes an evening. The real cost is ongoing ownership, including updates, backups and security, because an automation server holds credentials to everything it touches. Teams without a natural owner for that should honestly prefer hosted platforms.
Which handles complex logic better?
Both handle branching, iteration and error paths seriously. Make does it through a refined visual builder; n8n matches most of it visually and then goes further by letting you drop into real code when nodes run out of road. Pure visual sophistication favours Make; ultimate flexibility favours n8n.
What about data privacy?
Self-hosted n8n keeps workflow data and credentials entirely on your infrastructure, which is the strongest posture available and sometimes the deciding requirement. Make operates as a standard cloud platform under its commercial terms. If regulated data flows through your automations, that difference may make the decision for you.
Related comparisons
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Tool facts last checked August 2026