n8n vs Zapier vs Make: Which to Choose in 2026 (Pricing and Limits)
n8n, Zapier and Make compared on what they charge for, where they run, how they handle AI and who each one suits, with plan prices checked on 8 October 2026.
What matters most
- The biggest difference is what each tool counts. n8n bills per workflow execution, Zapier per task (each action step), and Make per credit (roughly each module run), so the same workflow can cost very different amounts at volume.
- n8n is the only one of the three you can self-host. Its free Community Edition runs on your own server, which matters when data cannot leave your environment.
- Zapier is the quickest to start and has the widest app catalogue. Make sits in between, with a visual canvas and finer control over data.
- For AI agents, n8n has the most built-in tooling. All three can call language models.
- Prices below were read from each vendor's pricing page on 8 October 2026. They change often, so confirm before you buy.
If you are choosing between n8n, Zapier and Make, the short version is this. Zapier is the fastest way to connect two apps. Make gives you more visual control for the same money. n8n gives you the most control and the only self-hosted option, at the cost of a steeper start. Which one is right depends less on features than on how many steps your workflows have, how often they run, and whether your data is allowed to leave your servers.
We build on all three for clients, with n8n as our default for anything that involves AI agents or sensitive data. We say so up front so you can weigh our view accordingly.
The quick comparison
| n8n | Zapier | Make | |
|---|---|---|---|
| What you pay for | Workflow executions | Tasks (each action step) | Credits (roughly each module run) |
| Self-hosting | Yes (free Community Edition) | No | No |
| Free tier | Self-hosted Community Edition; Cloud trial | 100 tasks a month | 1,000 credits a month |
| Entry paid plan | Starter, 20 EUR a month (2,500 executions) | Professional, from $19.99 a month (750 tasks) | From $9 a month (5,000 credits) |
| App catalogue | Hundreds of built-in nodes plus a generic HTTP Request node | More than 8,000 apps | 3,000+ apps |
| Best for | Technical teams, AI agents, sensitive data | Quick setups, non-technical users | Visual builders who want more control than Zapier |
Prices are as listed on each vendor's site on 8 October 2026. Zapier and n8n show annual-billing prices; Make does not state a billing period for its entry price.
Pricing: what each one actually counts
This is where most comparisons go wrong, because the three tools do not count the same thing.
n8n counts executions. One run of a workflow is one execution, however many steps it has. On n8n Cloud, Starter is 20 EUR a month for 2,500 executions and Pro is 50 EUR a month for 10,000. The Business plan, 667 EUR a month for 40,000 executions, is self-hosted only. All plans include unlimited users and workflows. The Community Edition is free to self-host: you pay for the server, not for n8n.
Zapier counts tasks. Each successful action step is a task, and the trigger does not count. Professional starts at $19.99 a month for 750 tasks, the Team plan at $69 a month for 2,000 tasks, and the free plan allows 100 tasks. Prices rise by task tier.
Make counts credits. Make moved from operations to credits as its billing unit. The free plan includes 1,000 credits a month and paid plans start at $9 a month for 5,000 credits. In general, each module that runs uses a credit, so a workflow with many modules uses many.
A worked example
Take a workflow with ten steps that runs 1,000 times a month.
- On n8n that is 1,000 executions, which fits comfortably inside the 2,500 of the Starter plan.
- On Zapier, nine action steps times 1,000 runs is about 9,000 tasks, which is well above the 750 or 2,000 task tiers and needs a larger plan.
- On Make, ten modules times 1,000 runs is about 10,000 credits, above the 5,000 on the entry plan.
The pattern is simple. The more steps a workflow has, the more n8n's per-execution pricing helps. For short two- or three-step workflows that run rarely, the three tools cost about the same and ease of use matters more.
Self-hosting and data control
Only n8n lets you run the software on your own infrastructure. For law firms, accountants, healthcare and anyone handling client data, that can decide the question: documents and records never pass through a third-party automation cloud. Self-hosting comes with duties. You keep it updated, backed up and secured, or you pay someone to.
Zapier and Make are cloud-only. Both are secure, established platforms, and for many companies that is fine. If you need a data processing agreement or specific data residency, read their enterprise terms before you commit.
Ease of use
Zapier is the easiest to learn. Its editor reads like a list of instructions, which is perfect for a trigger followed by a few actions and awkward once you need loops, branching and error handling.
Make uses a visual canvas of connected modules. It handles branching and data mapping better than Zapier and can get crowded with large scenarios.
n8n is a node-based canvas that behaves like a visual programming tool. You can drop in JavaScript or Python at any step. It rewards technical comfort, and a non-technical user will take longer to get going.
AI and agents
All three can call language models. n8n has the deepest built-in tooling for building AI agents: agent nodes, tool calling, vector store connections and memory. Make and Zapier have added AI steps and agent features, and they are strong for one-shot jobs such as summarising a document or classifying an email. If your plan is multi-step agents that retrieve company knowledge and call several tools, n8n is usually the more comfortable base. See our work on AI agents.
Zapier alternatives
If you are leaving Zapier, the usual reasons are cost at volume, the limits of linear workflows, or data control. The common destinations are:
- Make, if you want a visual builder with better data handling at a lower price per step.
- n8n, if you need self-hosting, complex logic, or AI agents.
- A custom build, when the workflow touches systems that none of the three connect to cleanly, or when reliability and audit trails matter more than speed of setup.
When to pick which
- Pick Zapier if you are non-technical, your workflows are short, and speed of setup matters most.
- Pick Make if you want visual control and clear scenario logic without self-hosting.
- Pick n8n if you have technical help, need self-hosting, run long or high-volume workflows, or are building AI agents.
- Pick none of them alone if the work crosses many systems, needs approvals and audit logs, or the cost of failure is high. That is a design problem first and a tool problem second, and it is the kind of job where a short audit saves a wrong turn.
Frequently Asked Questions
Is n8n better than Zapier?
For technical teams, high volume and AI agents, usually yes. For quick, simple automations built by non-technical staff, Zapier is easier. Neither is better in general, so match the tool to the workflow.
Is n8n really free?
The Community Edition is free to self-host, and you pay for the server and the time to maintain it. n8n Cloud and the Business plan are paid. Check the current plans on the vendor's site.
Why is Zapier more expensive than n8n at volume?
Zapier charges per task, and every action step counts. A long workflow that runs often uses many tasks. n8n charges per execution regardless of the number of steps, so long workflows cost relatively less.
Is Make cheaper than Zapier?
Often, for the same workflow, because Make's entry price is low and its visual builder handles more logic per step. The gap depends on how credits and tasks map to your steps, so run your own numbers using the example above.
Can I move from Zapier to n8n or Make?
Yes. Workflows have to be rebuilt rather than imported, so plan for testing. Migrate the most expensive or most fragile workflows first. We handle these moves as part of tech stack migration.
Which is best for AI automation?
n8n has the most built-in tooling for agents, but all three can call language models. The harder part is the knowledge, review steps and error handling around the model, not the platform choice.
Not sure which fits? Book a free AI audit and we will tell you, including when the answer is "none of them."
