n8n vs Make: Features, Pricing & Verdict

Make now bills in credits, not operations

If you last looked at Make before late 2026, the billing unit has changed. Make's help documentation, updated in October 2026, describes plans in credits rather than operations. For ordinary non-AI apps the conversion is one to one: one module operation costs one credit. AI modules cost more, with some content-extraction modules charging two or ten credits per operation, and Make's own hosted models metered by tokens.

The practical effect for a normal automation is unchanged, but it matters when you compare older articles, and it matters a lot if your scenarios lean on AI modules, where the real cost is no longer obvious from the step count.

The unit comparison

Make charges per module operation. n8n charges per workflow execution. A ten-module scenario run a thousand times a month costs about 10,000 credits on Make and exactly 1,000 executions on n8n. That tenfold difference in billable units is the heart of the comparison, and unlike a dollar comparison it is verifiable from both vendors' own documentation.

The dollar comparison is harder to make without guessing. Make publishes Core from $9, Pro from $16 and Team from $29 a month, each starting at 10,000 credits, but does not publish a price for any tier above 10,000 credits and does not state whether those figures are monthly or annual billing. Above the entry tier, nobody outside Make can tell you what high volume costs, so this page will not pretend to. Make's free tier gives you 1,000 credits a month, which is a useful way to test a scenario before paying.

Where Make is the better tool

The visual editor is the strongest in this category and it is not close. Scenarios are laid out spatially with data flowing visibly between modules, and for people who think visually that is a real productivity difference rather than a cosmetic one. Error handling and routing are easier to see at a glance than in most competitors.

Make also handles iterators, aggregators and nested data structures elegantly. If your work involves reshaping arrays of records, Make's built-in modules for that are better designed than reaching for a code step.

And like Zapier, Make is fully hosted. There is nothing to patch and nothing to back up, which for a small team without an infrastructure person is worth paying for.

Where n8n is the better tool

High volume, because of the per-run billing. Long scenarios, for the same reason. And self-hosting, which Make does not offer at all: if your data cannot leave your own servers, or you want an execution ceiling of "whatever the hardware can take", there is no Make equivalent of the free self-hosted Community Edition.

Code is the other dividing line. Make supports custom functions in places, but n8n treats code as a normal part of a workflow rather than an advanced feature, and will run JavaScript or, with external task runners, Python.

Both tools offer a startup discount of 50% for companies under twenty people, so if you qualify, factor that into either side of the comparison rather than just one.

The recommendation

Try Make's free tier and run a real scenario through it before deciding. If the visual model clicks for you and your volume is modest, Make is a pleasant tool to live in and the cost will stay reasonable. If your scenarios are long, your volume is growing, or self-hosting is a requirement rather than a preference, n8n's billing model will keep winning as you scale. The cost calculator will size the n8n side, and the alternatives page covers the open-source options if neither hosted tool fits.