Zapier vs Make vs n8n: which automation tool should you choose?

Choose Zapier if you want the largest app catalog and the easiest setup, Make if you want visual control over complex scenarios at a lower price per action, and n8n if you want to self-host, write code when needed, or run high-volume workflows where per-step billing gets expensive. This comparison covers AI features, pricing models, self-hosting and a pick per use case.

Zapier vs Make vs n8n: the short answer

Zapier is the easiest and most connected, Make is the most visual and usually cheaper per action, and n8n is the most flexible and the only one of the three you can self-host. Pick by who builds the workflows, how complex and frequent they are, and whether your data must stay on your own servers.

Prices and limits below are at the time of writing (October 2026); all three vendors change plans often, so confirm on their pricing pages before you commit.

How do Zapier, Make and n8n differ in pricing?

The three tools count usage differently, and that difference matters more than the list prices. Zapier counts tasks, Make counts credits, and n8n counts executions of a whole workflow, no matter how many steps it has.

Zapier: tasks

On Zapier's pricing page, a task is used when a Zap step completes an action, and some actions use more than one task. AI steps, code, MCP and the SDK all draw from the same shared task pool, and more powerful AI models or longer code runs use more tasks. Failed actions don't count.

• Free: $0, 100 tasks a month, two-step Zaps, Zapier Copilot.
• Professional: from $19.99 a month, multi-step Zaps, premium apps, AI fields.
• Team: from $69 a month, shared Zaps and folders, unlimited users.
• Enterprise: custom pricing, SSO, advanced admin and annual task limits.

Higher task tiers cost less per task. If you hit your limit, Zapier switches you to pay-as-you-go unless you turn that off.

Make: credits

Make bills in credits. Each action a scenario performs uses credits, usually one, while some AI features use more. Routers and error-handler modules don't use credits. A single run can use anywhere from two credits to thousands, depending on how many modules and items it processes.

• Free: 1,000 credits a month.
• Core, Pro, Teams: paid tiers priced by monthly credit volume, with more features at each step up and collaboration features on Teams.
• Enterprise: custom.

Annual billing is cheaper than monthly. Make's pricing page uses a credit slider, so check the price at your own expected volume.

n8n: executions

On n8n's pricing page, an execution is a single run of an entire workflow. The number of steps and the amount of data don't change the count.

n8n says annual billing saves 17% compared with monthly.

What this means for a real workflow

Consider a workflow with a trigger and eight steps (fetch a lead, enrich it, classify it with AI, update the CRM, post to Slack and so on) that runs 1,000 times a month.

• On Zapier, each action step uses at least one task, so this is roughly 8,000 tasks a month, more if the AI step uses a stronger model.
• On Make, each module action uses about one credit, so roughly 8,000 to 9,000 credits.
• On n8n, it's 1,000 executions, whether the workflow has 3 steps or 30.

This is rough arithmetic, not a quote. The pattern holds: per-action billing rewards short workflows, and per-execution billing rewards long ones. A two-step "new form entry to spreadsheet" automation costs about the same everywhere, while a 20-step enrichment pipeline that runs thousands of times a month can differ by an order of magnitude.

Which has the best AI features: Zapier, Make or n8n?

All three now let you add AI steps to workflows, build AI agents that pick their own next action, and connect to AI assistants through the Model Context Protocol (MCP). The differences are in control and cost rather than in which features exist.

Zapier AI

• AI steps and AI fields inside Zaps for summarizing, extracting and classifying.
• Zapier Agents, AI teammates you set up with prompts and company knowledge (FAQs, docs, links) that act across Zapier's 9,000+ apps, on command or while you're away. Templates include a support email agent and a lead enrichment agent.
• Zapier Copilot helps you build Zaps and agents from a description.
• Zapier MCP lets AI assistants such as Claude take actions in your connected apps.

Zapier's strength is reach: an agent or assistant can act in almost any SaaS tool your team uses, with no API work.

Make AI

• Make AI Agents run inside scenarios on the same canvas, next to fixed logic. According to Make's AI Agents page, they're available on all plans, each decision appears step by step in a Reasoning panel, and one agent can be reused across scenarios.
• Maia, an AI assistant for building scenarios.
• An MCP server that exposes scenarios to AI assistants.

Make's strength is visibility: you see each branch and each agent decision on the canvas, which helps when debugging.

n8n AI

• The AI Agent node connects a chat model to tools, and the agent decides which tools to call. See the n8n AI Agent docs.
• Memory, vector store and model nodes for building retrieval and chat workflows.
• The MCP Server Trigger node turns n8n workflows into tools that MCP clients can call, and an MCP client node lets agents use external MCP servers.
• Bring your own model, including local models on a self-hosted instance.

n8n's strength is control: you choose the model, see every intermediate step, add code anywhere, and keep data on your own server. Our n8n AI agent tutorial builds one step by step, and what is MCP explains the protocol all three now support.

Which is easiest to use?

Zapier is the easiest to learn, Make takes a few hours to get comfortable with, and n8n has the steepest curve, especially if you self-host. Ease matters most when the people building workflows aren't developers.

Zapier hides data structures from you, which makes simple things simple and complex transformations awkward. Make shows the data bundles flowing between modules, which is powerful once it clicks. n8n exposes the raw JSON at every step and lets you write code, which developers like and non-developers find intimidating at first.

Can you self-host Zapier, Make or n8n?

Only n8n can be self-hosted. Zapier and Make are cloud-only. If your data must stay on servers you control, for compliance or customer contracts, n8n is the only option of the three.

The n8n Community Edition runs with Docker:

docker volume create n8n_datadocker run -it --rm \ --name n8n \ -p 5678:5678 \ -e GENERIC_TIMEZONE="Europe/Berlin" \ -e TZ="Europe/Berlin" \ -e N8N_ENFORCE_SETTINGS_FILE_PERMISSIONS=true \ -v n8n_data:/home/node/.n8n \ n8nio/n8n

Then open http://localhost:5678. For production, n8n's docs cover running with PostgreSQL, a reverse proxy with HTTPS, and environment configuration.

What "free" self-hosting really costs

Self-hosting n8n removes the subscription, not the cost:

• A server, sized for your workflow volume and any AI work.
• Maintenance: updates, backups, monitoring, HTTPS certificates.
• Security: n8n holds credentials for every connected app, so a compromised instance exposes all of them.
• Your time, which is the biggest line item for small teams.

The n8n license

n8n's source code is public, but it isn't open source in the OSI sense. The Sustainable Use License lets you use and modify the software for your own internal business purposes or for personal and non-commercial use. Files marked .ee need an n8n Enterprise license. If you plan to offer n8n to customers as part of a paid product, read the license carefully or talk to n8n.

For a broader look at running these tools yourself, see our guide to self-hosting AI tools.

Zapier vs Make vs n8n: which should you choose?

Match the tool to the team and the workload, not to feature lists, because all three cover the common features now.

Many teams use two: Zapier for quick automations that business users own, and n8n for heavy pipelines that engineers maintain.

When to move beyond no-code automation

Visual tools get awkward when a workflow needs real business logic, tests, version control and code review. At that point a small script or service, written and maintained with an AI coding agent, is often simpler than a 60-node canvas. Our overview of no-code AI tools covers when to graduate, and AI automation examples shows workflows people run in both styles.

How to pick your automation tool this week

1. List your five most important automations with step counts and monthly runs.
2. Price them on Zapier (tasks), Make (credits) and n8n (executions).
3. Decide whether self-hosting is a requirement or a nice-to-have.
4. Build the same small workflow in your top two candidates; free tiers and the n8n Community Edition are enough.
5. Add one AI step and check how it's billed on the platform and by the model provider.
6. Pick the tool your actual builders found easiest, unless the cost gap is large.
7. Set usage alerts and review consumption after the first month.

If your automations grow into code that coding agents write and maintain, Orkio's Automation kit gives those agents an always-on cloud box to work on.

Frequently asked questions