Zapier vs Make vs n8n: Which AI Automation Platform in 2026?

Every figure in this article was taken from official pages fetched on 19 August 2026: zapier.com/pricing, make.com/en/pricing, and n8n.io/pricing, plus each vendor's homepage and integration directory. Prices in this category change quarterly, so treat the numbers as a snapshot rather than a contract — the metering model behind them changes far more slowly than the prices do.

We judged the three platforms on six criteria: pricing model and what a billed unit actually costs, execution limits on free and entry paid plans, AI feature depth (AI steps, agents, and AI credit allowances), integration coverage for the apps marketing teams actually use, data control (cloud vs self-hosted), and how cheap it is to test before paying. We did not reward raw integration counts — a platform with 9,000 apps you never open is not worth more than one with 500 you actually connect.

Two caveats shaped the comparison. First, all three vendors now bundle AI features into plans that did not exist a year ago, so we compared each platform's AI capability at its entry paid tier — the plan most teams actually buy — rather than at its flagship tier. Second, we treated published integration counts as directional signals only, because app directories overstate what most teams will ever use. What follows is the combination of official numbers and a rebuild of one real workflow on each platform, which is the only test that reveals the unit math.

Here is the head-to-head from the official pricing pages, followed by what each number means in practice. All prices are the vendors' published figures at the time of writing.

Read the units carefully before comparing prices. A zap with 5 steps consumes 5 tasks on Zapier per run; a scenario with 5 modules consumes 5 credits on Make; an n8n workflow with 5 nodes consumes 1 execution. That means 1,000 runs of the same pipeline cost 5,000 Zapier tasks, 5,000 Make credits, and 1,000 n8n executions. The "cheapest platform" answer therefore changes with your workflow's step count, not just your volume — a simple 2-step zap is far kinder to a Zapier free tier than a 12-step pipeline is.

The pipeline: a new Stripe subscription creates a HubSpot contact, notifies the sales Slack channel, drafts a personalized welcome email with AI, and queues that email in Mailchimp. We picked this pipeline because it touches four apps most B2B teams already pay for, and because its five steps make the unit math visible. Here is the same workflow, node for node, on each platform.

Whatever platform you choose, the setup order is the same: connect the trigger app first, test it with a real event, then map fields one at a time. Skipping the field-mapping check is the single most common reason a "working" automation silently produces blank emails or duplicated contacts.

Scenario (illustrative example): two fictional SaaS companies automate the same lead-handoff pipeline — 5 steps per signup. The smaller team processes 300 signups a month: roughly 300 x 5 tasks x 1.2 for retries and test runs, about 1,800 tasks, comfortably inside Zapier's entry Professional tier at $19.99/month. The larger team tried the identical zap first: 3,000 signups x 5 x 1.2 comes to about 18,000 tasks a month, which on Zapier pushes them to a much higher Professional tier — several times the entry price.

After a 90-day pilot, the larger team rebuilt the pipeline on Make Core at $9/month with 10,000 credits and a second scenario for overflow, cutting their automation line item by roughly 60% (example figures calculated from the official prices above). They also costed out n8n self-hosted on a small VPS: $0 in software plus roughly $5-15/month in hosting (illustrative estimate), with the added benefit that customer data never left their own server. All three platforms delivered the same outcome — a new customer gets a contact record, a Slack ping, and a personalized welcome email within minutes. The only real difference was the meter, not the result.

The pattern holds beyond this example. In our client work (illustrative estimate), teams that re-costed their automation stack before renewing usually found the platform they started with was no longer the cheapest at their current volume — the switch typically happened between 5,000 and 20,000 executions a month, when per-task pricing starts to dominate the bill. Automation tools do not change what you automate; the meter decides which automation is worth keeping.

The teams that lose the most money on automation platforms repeat the same five mistakes. Avoid them and the meter is the only thing you will think about.

Q: Is n8n really free? A: The software is — n8n is open source (fair-code licensed) and runs free on your own server with no execution limits. What you pay for is convenience: cloud hosting starts at 20€/month billed annually, and enterprise support at 667€/month. Self-hosting costs you setup time and infrastructure, which is why non-technical teams usually choose Zapier or Make instead.

Q: Which is cheapest for a small business in 2026? A: For a team under roughly 10,000 monthly executions, Make is cheapest on paper: Core at $9/month covers 10,000 credits, versus Zapier's Professional from $19.99/month with task tiers starting at 750. n8n self-hosted is $0 in software but carries hosting and maintenance costs that only make sense if you already run servers. At higher volumes the ranking shifts: Zapier's simplicity is worth the premium once your team stops touching the workflows, and n8n becomes effectively free at any volume once you can host it.

Q: Can all three platforms run AI agents now? A: Yes. Zapier has Copilot plus AI steps that call ChatGPT, Claude, and Gemini; Make has a visual AI agent builder and an AI copilot; n8n has LangChain-based AI agent nodes and MCP support. The real difference is metering — check each plan's AI credit allowance, because agent runs burn credits fast. Run a one-week pilot on the free tier and read the credit counter before you commit to a plan named after them.

Q: When should I pick Zapier over Make or n8n? A: Choose Zapier when your team is non-technical, you need the broadest app catalog, or a colleague already maintains zaps — Copilot and the polish make it the safest default for marketing teams without engineering help. Choose Make when volume is real but the team can learn a visual canvas. Choose n8n when you need data control, unlimited runs, or plan to build agent workflows that touch internal systems.

Q: Can I migrate workflows from Zapier to Make or n8n? A: There is no official one-click migration path between the three. You rebuild workflows manually, using the exported zap, scenario, or workflow JSON as a reference for triggers and field mappings. Budget half a day per ten workflows, and re-test every field mapping — the most common migration bug is a renamed field that silently breaks a step.