Zapier vs Make: Which Automation Tool Is Right for You?

Zapier and Make are the two tools most businesses compare when they start taking automation seriously. Both are cloud-hosted. Both connect thousands of apps. Both are built so the person running the business can set them up without a developer.

The real difference is not the feature list. It is what each one counts when it bills you, and that single fact decides both the monthly cost and how you should design the automation in the first place.

How They Work

Zapier builds workflows as a linear sequence: a trigger, followed by one or more actions, each with its own configuration panel. It is deliberately simple. The interface walks you through every step and you need almost no mental model to use it. That simplicity is Zapier’s genuine strength and also its ceiling.

Make (formerly Integromat) uses a canvas where you connect modules in a visual diagram. Data flows between modules along lines you can see. It supports routers, iterators, aggregators and parallel paths in a way that is visually obvious and structurally more flexible than a list of steps.

Neither is the no-code one any more. Zapier has a code step that runs JavaScript or Python, and Make has the Make Code app, which runs JavaScript or Python inside a scenario with its own sandbox and error logs. Any comparison that still says “Make has no code support” is out of date.

What Each One Charges For

This is the part to get straight before looking at a single price.

Zapier charges per task. A task is one successful action inside a Zap. The trigger is free. Every action bills, and so does every Path and Filter step, because they are steps in the Zap. A Zap that takes a form submission, looks up the customer, creates an invoice, emails it and posts to Slack spends four tasks every time it runs.

Make charges per credit. A credit is one module run. Make’s documentation is explicit that one operation equals one credit for standard modules, and the important part is what is excluded: routers, filters and error handlers consume nothing. Branching is free.

Make renamed this unit from “operations” to “credits” in August 2025. The help centre says plainly that plans and pricing, including the cost of credits, stayed the same, so an older article saying “operations” is describing the same thing. Two real changes sit underneath the rename:

• AI modules are variable. Credits for modules using Make’s automatic AI provider connections factor in token usage, not just the module run. An AI step is no longer predictably one credit.
• Make Code bills by time, at two credits per second of execution. Make notes most use cases finish inside one second.

The same workflow, both ways

Take a quote-request automation an Australian small business would actually build. A form comes in, the scenario checks whether the contact already exists, branches on the answer, creates or updates the CRM record, writes a row to a sheet, drafts a reply, sends it and posts to Slack. Six real actions plus one branch. It fires 1,000 times a month.

	Zapier	Make
Actions billed	6 actions + 1 Path step	6 modules, router free
Per run	7 tasks	6 credits
Per month	7,000 tasks	6,000 credits
Plan needed	Professional, 10,000-task rung	Core, 10,000 credits
Cost	about US$129/mo (~A$185)	US$9/mo (~A$13)

That is roughly A$170 a month, or A$2,000 a year, on one automation. The gap is not a percentage. It is a different order of magnitude, and it widens every time you add a branch, because Zapier charges for the branch and Make does not.

Pricing in 2026

Both bill in US dollars. AUD figures below are indicative, converted at US$1 = A$1.437, the rate on 16 October 2026.

	Price (billed annually)	Included volume	Unit
Zapier Free	US$0	100 tasks/mo, two-step Zaps only	task
Zapier Professional	from US$19.99/mo (~A$29)	750 tasks/mo, slider to 2 million	task
Zapier Team	from US$69/mo (~A$99)	2,000 tasks/mo, 25 users	task
Make Free	US$0	1,000 credits/mo	credit
Make Core	US$9/mo (~A$13)	10,000 credits/mo	credit
Make Pro	US$16/mo (~A$23)	10,000 credits/mo	credit
Make Teams	US$29/mo (~A$42)	10,000 credits/mo	credit

Three things the table does not say out loud:

Make’s paid plans do not differ on volume. Core, Pro and Teams all start at 10,000 credits. You move up for features, not capacity: Pro adds things like full-text execution search and custom variables, Teams adds shared folders and roles. Volume on any of them scales up from a slider on Make’s pricing page, and you can buy extra credits in bundles of 1,000 or 10,000. This is the most common misreading of Make’s pricing, including in comparison articles that list Pro as “40,000 operations” and Teams as “150,000”. It does not work that way.

Zapier’s plan name sets the features and the starting volume, not the price. Professional runs on a task slider from 750 tasks up to two million, so “Professional” can mean US$19.99 a month or several thousand. Common rungs billed annually are about US$49 at 2,000 tasks (~A$70), about US$89 at 5,000 (~A$128) and about US$129 at 10,000 (~A$185). There is no “Starter” plan any more, though plenty of articles still quote one.

Month-to-month costs more on both. Make Core becomes US$10.59, Pro US$18.82 and Teams US$34.12. Zapier is steeper: Professional goes from US$19.99 to US$29.99, roughly 50 per cent more at every rung.

Read the volume column with the unit column, never on its own. Zapier’s 750 tasks and Make’s 10,000 credits are not thirteen times apart in real capacity. Once you account for free routers and filters on Make, they are further apart than that.

Where Zapier Wins

Onboarding speed. For someone who has never used an automation tool, Zapier is the fastest route from nothing to a working automation. The interface is more constrained, which also makes it less overwhelming. If the goal is to have one thing running this afternoon, Zapier wins and the price difference is irrelevant.

Integration breadth. Zapier connects more than 9,000 apps against Make’s 3,500-plus. For mainstream platforms both cover you completely. Zapier’s advantage is the long tail: a niche booking system, an Australian industry SaaS, a tool with a Zapier integration and no public API. If one system you cannot work without falls in that gap, Zapier wins the whole decision on that single connection.

Volume of tutorials. Zapier has been around longer and has more templates, guides and community answers for common tasks. When you are stuck at 9pm, that matters more than it should.

Where Make Wins

Branching and routing. Make’s canvas handles conditional paths, parallel branches, loops and error routing more cleanly than a linear builder, and the flow-control modules are free. If your automation has to do different things depending on the data, Make is easier to build and cheaper to run.

Data transformation. Parsing arrays, aggregating results, restructuring objects. Make’s iterators and aggregators are built for this and Zapier works around it.

Cost at every volume above the free tier. Not slightly. Multiples, as the worked example above shows.

Visual clarity as workflows grow. Once the canvas clicks, a complex scenario is genuinely easier to reason about than the equivalent twelve-step Zap, because you can see the whole shape at once.

AI: Both Do It Now, The Billing Differs

The old line that Make’s AI is shallow and Zapier’s is basic is no longer true of either.

Make has AI Agents that connect across its 3,500-plus apps with visible reasoning and tool use, plus an MCP server that turns your scenarios into tools an assistant like Claude or ChatGPT can call. Zapier has AI by Zapier, AI fields, Agents and its own MCP support.

Where they part ways is the meter:

• Make charges credits for AI modules that factor in token usage when you use its automatic provider connections. Bring your own OpenAI or Anthropic key and the module is one credit while the model bill goes to the provider directly.
• Zapier applies a task multiplier by model tier. A Standard AI step counts as 1 task, Advanced as 3 and Premium as 5, with new AI steps on paid plans defaulting to Premium. Tool calls multiply at the same rate, so one Premium step making three tool calls spends 20 tasks.

For occasional AI steps inside an otherwise normal automation, neither will hurt. For AI agent work that reasons and calls tools on every run, per-action billing compounds fast on both, and that is the point at which n8n and its per-execution model becomes the serious option. n8n vs Zapier works that maths through properly.

Which to Choose

Choose Zapier if:

• You need a specific integration Make does not have
• You want something live today with no learning curve at all
• Your volume is genuinely tiny, a few hundred actions a month, where the free tier covers it
• Nobody in the business has a few hours to learn a canvas

Choose Make if:

• Your workflows branch, loop or transform data
• You are past the free tier and paying for volume
• You plan to build several non-trivial automations over time
• You want the lower bill without taking on a server

For most businesses comparing just these two, Make is the better long-term choice. The pricing advantage is real and large, the complexity ceiling is higher, and the learning curve is a day, not a project. Zapier earns its price on breadth and speed to first automation, which are real things, but they are front-loaded benefits you stop collecting after week one.

The honest caveat: this comparison has a third answer. If your data has to stay on your own infrastructure, or you are building AI agents, neither of these is the tool. Zapier vs Make vs n8n puts all three side by side, and Zapier alternatives covers the wider field including Power Automate and the flat-fee options.

---

Not sure which platform to build on? WhatWill AI scopes and builds workflow automation for Australian businesses. Book a call and we will tell you what is worth building and what to build it on, including when the answer is to stay where you are.