Platform comparison

n8n vs Zapier vs Make: Which Automation Platform Fits Your Team?

An operator's comparison of the three platforms Operator Intelligence builds on: how each one bills, where each one strains, and which to pick for your volume, logic and data.

By Chad Westleigh · Updated October 17, 2026

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n8n vs Zapier vs Make: the short verdict

n8n vs Zapier is the comparison most teams start with, and Make belongs in the same conversation. All three connect your apps and run workflows without an engineering team. They differ in billing, logic depth, where your data lives and AI tooling.

As of October 2026, Zapier is the right default for a few simple, linear workflows with a non-technical owner. Make suits branching, mid-complexity scenarios owned by an operations generalist. n8n suits long, high-volume or data-sensitive workflows and complex AI steps, and asks more of whoever maintains it. If you want the build handled for you, see our AI automation consulting service.

n8n vs Zapier vs Make comparison table (October 2026)

Plan details come from each vendor's own pricing and documentation pages in October 2026. Plans change often, so confirm current terms before you buy.

Factor	n8n	Zapier	Make
Billing unit	Executions: one full workflow run, however many steps	Tasks: each successful action step; triggers and built-in tools such as Filter and Formatter don't count	Credits (replaced operations on August 27, 2025): most module runs use one; some AI features use more
Free or entry allowance	Free self-hosted Community Edition; cloud Starter includes 2,500 executions a month	Free plan with 100 tasks a month	Free plan with 1,000 credits a month
Self-hosting	Yes: your server, your cloud or on-premises	No, cloud only	No, cloud only; Enterprise adds an on-prem agent for local networks
Integrations	500+ built-in, plus community nodes and an HTTP Request node for any API	9,000+ apps, the largest catalog	3,000+ native apps, plus custom apps for public APIs
AI agent features	AI Agent node with model, memory and tool sub-nodes; swap models without a rebuild	Zapier Agents, AI steps in Zaps, Copilot and AI Guardrails	AI Agents and AI Toolkit, on Make's AI provider or your own OpenAI or Anthropic key
MCP support	MCP Client Tool calls external servers; MCP Server Trigger exposes a workflow as tools	Zapier MCP lets Claude, ChatGPT or Cursor run Zapier actions; each tool call uses two tasks	MCP server exposes scenarios as tools; MCP client lets Make agents call outside tools
Learning curve	Steepest: data structures, expressions, light code	Gentlest: linear steps in plain language	Moderate: routers, iterators and data mapping
Governance	SSO, LDAP, environments and Git version control on Business; log streaming on Enterprise	SAML SSO and 6-month audit log on Team; SCIM and 1-year audit log on Enterprise	SSO, role-based access and audit logs on Enterprise
License	Sustainable Use License (fair-code): free for internal business use, not OSI open source	Proprietary cloud service	Proprietary cloud service

Tasks vs operations vs executions: how the pricing models differ

The billing unit matters more than the sticker price, because it decides how cost grows as workflows lengthen and run more often.

Zapier counts a task for each successful action step. Triggers, Filter and Paths steps don't count.
Make counts a credit for most module runs, including each trigger check, even one that finds nothing new. Routers and filters don't count.
n8n counts one execution per full production run, however many steps it has. Manual test runs and sub-workflows don't count.

The pattern: Zapier is economical for short, low-volume workflows, Make sits in the middle, and n8n pulls ahead as workflows lengthen and volume climbs. AI adds a second meter on every platform, paid through the vendor or your own model account, so we price both against your real volumes before recommending anything. The worked example below shows the math.

Worked cost example: one workflow at 10,000 runs a month

Billing-unit math as of October 2026, from each vendor's own help and pricing pages. The workflow: a webhook trigger, a filter, then four actions (look up the CRM record, classify the request with Claude through your own API key, update the CRM, post to Slack), handling one item per run. We show units, not dollars: find the tier that covers these units on each vendor's current pricing page, because tiers and prices change often. Model tokens for the Claude step are billed by Anthropic to your account on all three platforms.

Platform	Billing unit	Units per run	Units at 10,000 runs a month	What changes the count
Zapier	Tasks	4: one per action; the trigger and the filter are free	About 40,000 tasks	Using AI by Zapier instead of your own Claude key costs 1, 3 or 5 tasks per AI step, by model tier
Make	Credits	5: the trigger plus four modules; the filter is free	About 50,000 credits	A scheduled poll instead of a webhook adds a credit per check, even when nothing is new; Make's own AI provider bills by tokens in credits
n8n	Executions	1: the whole run	10,000 executions	Adding steps doesn't change the count; splitting one process across several triggered workflows does

Self-hosting n8n: when data control is worth the upkeep

Self-hosting is the clearest functional difference between n8n and the other two. n8n can run on your server, in your cloud account or on-premises, which keeps workflow data and credentials inside your environment. For teams handling client files, financial records or contracts that restrict where data goes, that can settle the decision.

Self-hosting still costs something: someone has to patch, back up, monitor and secure the server. n8n's Sustainable Use License allows free internal business use, but offering n8n to your own customers as a hosted product needs a separate agreement. Our rule of thumb: self-host when data or volume justifies it and a named person owns the server; otherwise start on n8n Cloud. Our n8n consulting work covers either setup.

AI agents and MCP in n8n, Zapier and Make

All three platforms now ship AI agent features and support MCP (Model Context Protocol), the open standard AI applications use to call tools. n8n lets you assemble an agent node by node, choosing the model, memory and tools, and keep the rest of the workflow deterministic. Zapier gives agents its 9,000+ app catalog. Make sits between them.

Beyond a single AI step such as classification or a drafted reply, we usually build agent logic in n8n or in code, with a person approving actions that matter. See custom AI agent development for how we build agents, and MCP vs API for how MCP relates to the integrations you already have.

Choose n8n, Zapier or Make: verdicts by use case

Decide per workflow. Plenty of lean companies run two of these side by side.

Choose Zapier when…

You have a few simple, linear workflows, a non-technical owner, or an app that connects most reliably through Zapier. Speed to the first automation matters more than cost per run.

Choose Make when…

A non-developer owns the workflow, the logic branches and loops, and volume is moderate. The canvas keeps complex scenarios readable without code.

Choose n8n when…

Volume is high, workflows are long, data must stay in your environment or the AI logic is complex. Budget for a technical owner or a support partner.

Learn more

Run two platforms when…

Marketing lives in Zapier while operations needs n8n's volume and control. Document every workflow with a named owner, wherever it runs.

n8n vs Make: the closer call

n8n vs Make is a closer contest than either is with Zapier, because both handle branching, loops and data transformation well. Three questions usually decide it:

Who maintains it? Make's canvas suits an operations generalist; n8n rewards someone comfortable with JSON, expressions and the odd code node.
How long and frequent are the runs? Make bills per module run and n8n per execution, so long, high-volume workflows favor n8n.
Where must the data live? Only n8n self-hosts.

When the answers conflict, we default to the platform the long-term owner can maintain. A cheaper workflow nobody can fix is not cheaper.

A real n8n build: Mail New England file validation

Mail New England, a direct mail company, needed every client zip code selection file checked before print. Operator Intelligence built an n8n workflow integrated with Google Sheets and Gmail: a client submits a file online, an AI step validates it against a master, the workflow emails the client exact error details, and corrected files route to the print team.

It is a typical n8n-shaped job: a multi-step loop on every submitted file, with one AI step and deterministic routing around it. The three-week build removed about 20 hours a week of manual review and delivered a 100% file error reduction. Read the Mail New England case study.

“...this automated workflow completely removed that entire process from our team's hands, freeing them up to focus elsewhere.”

Wendi Smith, VP, Mail New England

Questions to answer before you choose a platform

How many runs per month, and how many steps per run?
Who will own and fix each workflow after launch?
Does each platform maintain the integrations you need?
Which steps need AI judgment, and whose model account pays?
What do you need for SSO, audit logs and access control?

Hiring a Zapier consultant, Make.com consultant or n8n consultant

A good automation consultant maps the process before opening any platform, and doesn't recommend the same tool for every job. Insist that workflows, credentials and documentation live in your accounts, that failures alert a named owner, and that whoever maintains each workflow gets trained.

Operator Intelligence works as a Zapier, Make.com and n8n consultant on those terms. Not sure what to automate first? Start with the free AI readiness assessment.

Moving existing Zaps or Make scenarios to n8n is a rebuild rather than an export, because n8n doesn't document an official importer. Our step-by-step Zapier or Make to n8n migration guide covers inventory, parallel runs and cutover.

Frequently asked questions

Is n8n cheaper than Zapier?

Usually, for long or high-volume workflows, because n8n bills per execution and Zapier per action step. For a few short Zaps at low volume, Zapier can cost less overall once you count the time to maintain n8n.

Is Make cheaper than Zapier?

It can be, but compare cost per run rather than plan prices. Make uses a credit for most module runs, including the trigger; Zapier uses a task per action step but not for the trigger or built-in tools. Multiply each by your monthly runs at the tier you'd need.

Is n8n open source?

Its source code is public and the Community Edition is free to self-host, but n8n uses the Sustainable Use License, a fair-code license rather than an OSI-approved one. Internal business use is allowed.

Which platform suits AI agents: n8n, Zapier or Make?

All three offer agent features and MCP support as of October 2026. n8n gives node-level control inside a workflow, Zapier the widest app reach, and Make a visual middle ground. For agents that take consequential actions, we add human approval steps on any platform.

Can we migrate from Zapier to n8n?

Yes. We inventory your Zaps, group them by business process and rebuild each process as one n8n workflow with error handling, running old and new side by side until outputs match. The full sequence is on our n8n consulting page, and our AI automation service handles migrations between any of the three platforms.

Pick the right platform for your next workflow

Tell us the workflow, the monthly volume and who will own it. We'll recommend a platform with the cost math, and build it if you want.

Book a scoping call

Sources

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