n8n vs Make.com: Which One Is Cheaper for Your Workflow?

Almost every n8n vs Make.com comparison answers the wrong question. They line up the interfaces, count the integrations, note that one is open source, and leave you no better placed to decide than you were before. The difference that actually determines which platform you should be on is duller and far more useful: the two platforms count different things when they bill you.

n8n charges for a workflow run. Make charges for every module inside that run. Feed the same automation into both and the bills diverge by a factor that depends entirely on how many steps sit inside one execution. Once you know that number for your own workflows, the choice mostly makes itself.

All figures below were read off each vendor's own pricing page on 13 August 2026. Both move, so check them before committing. If Zapier is still in the mix, Make.com vs Zapier for Small Business covers that comparison separately, and the developer-side view of this same pairing is in Make.com vs n8n: A Developer's Honest Take.

The one difference that decides it

n8n's pricing page states its model plainly: pricing is based on monthly workflow executions "regardless of complexity", and every tier is described as "workflow executions with unlimited steps". An execution is one run of the whole workflow. Three nodes or ninety, it costs the same.

Make counts the other way. Its credits documentation sets out that for non-AI apps, one operation equals one credit, and an operation is one module doing one thing. A twelve-module scenario that runs once costs twelve credits. The same scenario run a thousand times costs twelve thousand.

Everything else in this comparison is a tiebreaker. This is the decision.

What each platform charges

n8n Cloud

Two things to read carefully. The page renders in euros only and defaults to the annual-billing position, with a monthly toggle that costs more; the annual saving is advertised at 17 per cent. And the Business tier is labelled self-hosted, so it is not a like-for-like cloud row with the two above it. Business overages are charged at 4,000 EUR per additional block of 300,000 executions, and n8n states that workflows keep running past quota rather than stopping.

There is also a Community Edition that is free to self-host indefinitely, which changes the arithmetic completely. More on that below.

Make

Make's pricing page carries both a monthly/annual toggle and a credit slider, so any figure you quote depends on where both were sitting. The entry prices above come from the page as it renders by default. Run your own numbers through the Make.com Pricing Calculator rather than trusting a table anyone wrote down, including this one.

One thing worth knowing before you plan around a tier: if you overshoot your allowance, extra credits cost 25 per cent more than the credits included in your plan, whether you buy them manually or let auto-purchasing do it. Make's own release note on the change recommends moving up a tier instead, because higher tiers carry a lower per-credit cost.

Work out your own crossover

This takes two minutes and is worth more than any comparison table.

Count the modules in a typical scenario. Multiply by how many times it runs in a month. That is your Make credit consumption. Now take the same run count on its own, ignoring the modules. That is your n8n execution consumption. Price both.

The unit costs at entry level are roughly:

• n8n Starter: 20€ for 2,500 executions is 0.008€ per execution.
• Make Core: $12 for 10,000 credits is $0.0012 per credit.

Those are different currencies and the rate moves, so treat what follows as approximate rather than exact. At anywhere near parity, the crossover sits at about seven modules per run. Below that, Make's per-module model is cheaper. Above it, n8n's flat-rate execution wins, and it wins by more the deeper your workflows get.

That single number explains a lot of otherwise confusing advice. People running short, high-frequency automations swear Make is cheaper. People running long enrichment and processing chains swear n8n is. Both are right about their own workflows.

Two worked examples

A deep workflow. An order-processing automation with twelve steps: webhook trigger, validate, look up the customer, branch on order value, enrich from two APIs, write to a CRM, write to a sheet, format a message, send it, log the result. It runs 1,500 times a month.

On Make that is 12 × 1,500 = 18,000 credits. Core's entry allowance of 10,000 does not cover it, so you either slide the tier up or absorb 8,000 extra credits at the 25 per cent uplift, which is roughly $12 on top of the $12 plan. Call it $24 either way.

On n8n that is 1,500 executions. Starter's 2,500 covers it with room to spare, at 20€ billed annually. The twelve nodes cost nothing extra. Add another six nodes tomorrow and the bill does not move.

A shallow workflow. A form-to-Slack notification: webhook, format, post. Three modules, firing 9,000 times a month.

On Make that is 27,000 credits, which sits comfortably inside a Core plan with the slider moved up. On n8n that is 9,000 executions, which blows through Starter's 2,500 entirely and pushes you onto Pro at 50€. Here Make is clearly the cheaper platform, and it is not close.

Same two platforms. Opposite answers. The only thing that changed was the shape of the work.

Where the arithmetic stops being the answer

Concurrency. n8n Starter runs five executions at once, Pro twenty. If your trigger fires in bursts, that ceiling will bite before your execution allowance does. Make's Free plan sets a 15-minute minimum interval on scheduled scenarios, which rules it out for anything that needs to feel responsive.

History and debugging. n8n Starter keeps seven days of execution logs and 2,500 saved executions; Pro keeps thirty days and 25,000. When something fails silently on a Friday and you look on Monday, retention is the difference between a diagnosis and a guess.

AI steps break the arithmetic on both sides, differently. On Make, AI modules using Make's own AI provider are billed dynamically against a token-to-credit table rather than at one credit per run, so a scenario built around an LLM call eats an allowance far faster than its module count suggests. If you connect your own OpenAI or Anthropic key instead, you pay Make one credit for the operation and your provider directly for the tokens.

On n8n, be careful with the word credit. n8n's plans include "AI credits" — 2,300 on Starter, up to 13,700 on Pro — and these are AI Assistant credits for the in-editor build assistant. They are not model tokens and they are not a billing unit for your workflow runs. Several comparison articles treat the two platforms' credits as the same thing. They are not remotely the same thing.

Self-hosting changes the question entirely

n8n's Community Edition is free to self-host for as long as you like, and n8n's guide to its editions sets out what each one includes. Run it on a small VPS and the per-execution arithmetic above stops applying — your cost is the server, and n8n Self-Hosted Setup covers what that involves.

Make has no self-hosted option at all. If data residency or cost at very high volume is the constraint, that is the end of the comparison.

Two caveats before you treat free as free. n8n's licence is not a standard open-source licence and it restricts what you may do commercially, which matters a great deal if you are an agency thinking about hosting instances for clients. And the Community Edition deliberately withholds a list of features that includes Git version control, environments, SSO and project sharing. Both points are covered properly in Make.com vs n8n: A Developer's Honest Take, which is the piece to read if self-hosting is genuinely on the table.

Interface, handover and app library

Make's canvas is the easier one to hand to somebody else. Circular modules on an infinite canvas, mapping in a side panel, and most people can build something useful in their first hour — Make.com Tutorial for Beginners walks through that first build. n8n's node canvas is a developer tool by temperament, rewarding anyone comfortable with JSON structures and expressions, and How to Build an n8n Workflow covers the equivalent first build.

On integrations, Make has the broader native library. For an obscure SaaS tool, Make is more likely to have a proper connector where n8n would have you configuring an HTTP request. For anything mainstream, both have what you need.

Side-by-side summary

So which one should you use?

Choose Make if your scenarios are short, if a client's own team will open and edit them, if you want a managed service with no server to think about, or if you need a native connector for something unusual.

Choose n8n Cloud if your workflows are deep enough that per-module billing punishes you, if you need code nodes, or if you want the option of moving the same workflows onto your own infrastructure later without taking on server administration today.

Choose self-hosted n8n if volume is high, if a client has data residency requirements, or if you are technical enough that the maintenance is genuinely cheap for you. Read the licence first.

I use both. Most client work runs on Make, because the interface is the one I can hand over and explain, and because client scenarios tend to be shallow enough that per-module billing is not the constraint. My own high-volume infrastructure runs on self-hosted n8n. The No-Code Tool Comparison Matrix covers both alongside other options if you want a wider view, and the Zapier Cost Calculator is there if Zapier is still the incumbent you are pricing against.

If you want a second opinion on a specific build, book a free 30-minute call. Bring the workflow and its run frequency and we can price both sides properly.

Frequently Asked Questions

How do I know how many modules my scenarios average?

Divide, do not count. Take last month's total credit consumption from your Make dashboard and divide it by the number of scenario runs over the same period. That gives you a real average across everything you run, weighted by how often each scenario fires, which is the number that actually determines your bill. Counting modules by eye tends to overweight the big impressive scenario you built last week and underweight the three-module one quietly firing every four minutes.

Are n8n's AI credits the same as Make's credits?

No, and conflating them is the single most common error in this comparison. Make's credits are its billing unit for everything. n8n's AI credits are an allowance for the AI Assistant that helps you build workflows in the editor, currently in preview and Cloud-only. They do not pay for your workflow runs, they do not buy model tokens, and they cannot currently be topped up. If a comparison table puts the two in the same column, treat the rest of it with caution.

Is self-hosted n8n really free?

The software is free to run and always has been. The licence is the part people skip. It permits internal business use and personal use, but it is not an OSI-approved open-source licence and it does not permit you to resell n8n as a hosted service to others. If you are an agency planning to run client instances as a product, that is a conversation with n8n rather than a decision you make on your own. Some features are also held back from the Community Edition entirely.

What actually happens when I go over my allowance?

Different failure modes, worth knowing in advance. Make will sell you extra credits at a 25 per cent premium over your plan rate, automatically if you have enabled auto-purchasing, and its own documentation suggests you would be better off moving up a tier. n8n keeps your workflows running and invoices the overage afterwards, which on the Business plan means 4,000 EUR per additional 300,000 executions. Neither platform silently stops your automations, but neither is a cheap way to discover you sized the plan wrong.

Can I move a workflow from one to the other?

Not mechanically. There is no converter, and the two platforms model data differently enough that a translation would mislead you even if one existed. What does transfer is the design: the trigger, the branches, the error paths, the decisions about what happens when an API is down. That is most of the thinking, and rebuilding a scenario you already understand is usually an afternoon rather than a project. Plan for it as a rebuild, not an export.

If you would rather have this built than build it, I take on Make and n8n work through Fiverr and Upwork.