n8n vs Zapier vs Make: the pricing model is the decision

The three tools bill on completely different units: per step, per module, and per execution. That single difference decides the cost at scale, and it is why teams get surprised by the invoice rather than the features.

The three price models, which is the whole decision

These tools look similar and bill on completely different units, which is why teams get surprised by the invoice rather than the features.

Zapier bills per step. A five step automation that runs 1,000 times consumes 5,000 tasks. Professional starts around $29.99 a month billed monthly, or about $19.99 annually, for 750 tasks. Cost scales with how elaborate each automation is, not just how often it runs.

Make bills per module. Its Core plan starts around $9 a month for 10,000 credits. Because the unit is smaller and cheaper, multi step logic that would be expensive on Zapier is often affordable here.

n8n bills per execution, or not at all. Cloud plans start around $20 a month and count workflow executions rather than steps, so a twenty step workflow costs the same as a two step one. Self hosted removes the platform fee entirely. At high volume that difference is reported to cut costs by 80 to 90 percent.

The practical rule: if your workflows are short and infrequent, per step pricing is fine. If they are long or run constantly, per execution pricing wins by a margin that grows with scale.

What each is actually good at

Zapier has the widest connector library and the shallowest learning curve. A non-technical person can ship something useful in an afternoon. That matters more than engineers usually admit, because the alternative to an imperfect Zap is often a manual process that nobody automates at all.

Make gives you a visual canvas with branching, iteration, and error handling that Zapier's mostly linear model makes awkward. For multi step logic with conditional paths it is the better tool and usually the cheaper one.

n8n is the engineering option. It self hosts, so your data stays in your environment, which is the deciding factor in regulated settings. It has proper version control, JavaScript when you need it, and error handling that behaves like software rather than a setting. The cost is that someone has to own it.

The support question nobody asks until it breaks

On Zapier and Make you file a ticket. On self hosted n8n, the answer is you, backed by a community. That is a fair trade when you have engineering capacity and a poor one when a finance close depends on a workflow and the person who built it has left.

Price the operational ownership, not just the licence. A self hosted tool with no named owner is cheaper on the invoice and more expensive the first time it fails quietly.

What most companies actually end up doing

They run two. Zapier or Make where business teams self serve and speed matters more than unit cost, and n8n where volume, compliance, or data residency says otherwise.

That is not indecision. It reflects that these tools serve different users. Forcing a marketing team onto self hosted n8n to save on licences usually produces fewer automations, not cheaper ones.

Where AI changes the calculation

All three now offer AI steps, and the differences matter once a model is in the loop. The question stops being which tool connects to more apps and becomes which one lets you handle a model returning something unexpected. That is error handling, retries, and conditional escalation, which is where Make and n8n are meaningfully ahead.

If the AI step is the point of the workflow rather than a garnish, weight branching and failure handling far above connector count.

How to choose without a three month evaluation

Take your three most important existing automations and answer two questions. How many steps does each have, and how often does each run. Multiply those out against the three price models using your real numbers rather than a vendor calculator. Then ask who fixes it at 6pm on a Friday.

Those two answers decide it faster than any feature matrix.

Frequently asked questions

Is n8n actually cheaper than Zapier?

At low volume, no meaningfully. At high volume, yes and by a wide margin, because n8n bills per workflow execution rather than per step and self hosting removes the platform fee entirely. Reported savings at scale run 80 to 90 percent. The offset is that someone has to own the instance.

What is the difference between Zapier and Make?

Zapier bills per step and has the wider connector library and the gentler learning curve. Make bills per module, costs less per unit of work, and handles branching, iteration, and error handling that Zapier's largely linear model makes awkward. For a two step handoff Zapier is usually right; once there are conditional paths, Make is the better tool.

Which one is best for AI workflows?

Whichever handles failure best, because the hard part of an AI step is not calling the model but deciding what happens when it returns something implausible. That favours Make and n8n, which offer real branching, retries, and conditional escalation.

Should we standardise on one tool?

Most companies do not, and that is usually the right answer. Zapier or Make where business teams self serve, n8n where volume, compliance, or data residency demands it. Forcing one tool on every team tends to reduce the number of automations rather than the cost of them.