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Robert Breen
Robert Breen

Posted on Originally published at learn.ynteractive.com

n8n vs Make: Credits, Executions, and Where the Cost Curves Cross

Make and n8n look almost the same from ten feet away. Both show your workflow as boxes joined by lines on a canvas. Both connect Gmail and Google Sheets without code. Both have a free way to start.

The difference shows up on the invoice, and it comes down to one design choice: what gets counted as one unit of usage.

All prices here are from each vendor's own pages as of October 2026. They change, so confirm on the current pricing pages.

What Make counts

Make counts credits. Most actions cost one credit. Reading, searching, creating, updating or deleting app data costs a credit. So does reading from a webhook and a built-in data transformation. The Router module and error handlers are not counted. Make also notes that some AI features can use more than one credit per action.

What n8n counts

n8n counts executions. One execution is one run of the whole workflow, no matter how many steps are inside it. If you have ever been billed per API call versus per session, this is the same split.

Round one: a short workflow

Take a workflow that starts from a new form entry and then does four things: an AI step, a Google Sheets row, an email and a Slack message. Call it five module actions per run. It runs 500 times a month.

  • Make: roughly 2,500 credits (five actions, 500 times). That fits in the 10,000-credit amount Make's slider starts with, at $12 a month billed annually on the Core plan.
  • n8n: 500 executions. That fits inside Starter's 2,500, at 20 euros a month billed annually.

Make wins this round on price. For light use, it is often the cheaper tool, and the Core plan also gives you unlimited active scenarios and scheduling down to the minute.

Round two: a longer workflow

Now stretch it. Ten steps, running 2,000 times a month.

  • Make: about 20,000 credits.
  • n8n: still 2,000 executions, inside Starter's 2,500.

This is where the curves cross. Make's number scales with steps times runs. n8n's number scales with runs only. The more steps inside a workflow, and the more steps inside loops, the more n8n's per-run counting helps.

I want to be honest about the limits of this example. It is a made-up workflow, the currencies differ (dollars for Make, euros for n8n), and I did not run either one under load for this article. Use Make's pricing slider and n8n's pricing page with your own step counts. The shape of the curve is the takeaway, not my exact totals.

What the free plans give you

  • Make Free: 1,000 credits a month, routers and filters, and a 15-minute minimum interval between runs. Unlimited active scenarios and minute-level scheduling start on paid Core.
  • n8n: the Community Edition is free to self-host, and an n8n Cloud trial needs no credit card (1,000 executions, Pro-level features).

Make's free plan including routers and filters is a real plus. You can build a branching scenario without paying.

Self-hosting is the other big fork

You can host n8n yourself. Make runs only as a hosted service. If you have someone who can patch a server, back it up and lock it down, self-hosting keeps workflow data on your own infrastructure. n8n's docs are direct about this: with self-hosting, the infrastructure is your responsibility and technical knowledge is required.

If you do not want a server, n8n Cloud and Make are both hosted for you, and for most small offices that is the less stressful route.

AI agents

n8n's AI Agent node lets you attach a chat model, memory and tools such as Google Sheets in one place. The agent's inner steps do not raise your execution count. Make has AI features too, and if you only need one AI step inside a short scenario, either tool works fine.

Remember the second bill either way. The AI model itself, such as the OpenAI API, is billed by its provider and is separate from any ChatGPT subscription.

Integrations and privacy, briefly

Make lists 3,500+ apps on its plan page. n8n lists 2,367 integrations plus an HTTP Request node, so the raw count matters less than whether your specific apps are covered. Check both directories for the apps you use.

On security, Make says it has completed SOC 2 Type II and SOC 3 audits, runs an ISO 27001 certified program and adheres to GDPR, with log data stored for 30 days by default. n8n says its Cloud is hosted in the EU and its program aligns to SOC 2. Either way, send only the fields a workflow needs.

How I would choose

  • Short or medium scenarios, a low entry price, scheduled jobs: Make.
  • Long workflows, AI agents, high volume, or a possible self-host later: n8n.
  • Not sure: build the same small workflow in both before paying. Triggers, field mapping, filters and testing with sample data are the same ideas, so the second tool takes far less time.

Practice it free

Both lessons run in a practice copy of the tool, so nothing touches your real accounts:

Disclosure: Stepthrough has an affiliate relationship with n8n, so I may earn a commission if you sign up through an n8n link on Stepthrough. There are no affiliate links in this article.

Full comparison with prices, FAQs and sources: n8n vs Make: Which Automation Tool Fits You (2026)

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