Short answer: n8n wins for technical teams that want self-hosting, deep AI agent flows, and predictable cost at scale. Make wins for ops people who need a strong visual canvas with affordable scenario pricing. Zapier wins for non-technical teams that need the largest app catalog and zero learning curve. The rest of this article is the long version of that sentence — with prices, tables, and the trade-offs that actually matter.
If you've been picking automation platforms for any length of time, you've watched the landscape flip twice: first from "Zapier or nothing" to a real three-way race, and then from "automation tools" to "AI orchestration tools." Most comparison articles are still stuck in 2022. This one isn't.
What is each platform, in one paragraph?
Zapier is the original consumer of the category. Trigger → action, simple language, an app catalog of around 7,000 integrations, and a per-task pricing model that rewards low-volume use cases. It's the platform your marketing manager can use without filing a ticket.
Make (formerly Integromat) is the visual-first European challenger. You build "scenarios" on a 2D canvas with bundles of data flowing between modules. It's more powerful than Zapier on data manipulation, cheaper at volume, and significantly more enjoyable to debug. Around 2,000+ apps, but the modules are deeper.
n8n is the open-source, self-hostable workhorse. You can run it for free on your own server, plug into 500+ native integrations plus arbitrary HTTP, and build full AI agent flows with native LangChain-style nodes. It's the platform your dev team picks when they want automations to live next to the rest of the stack — versioned, observable, and not bound by per-task fees.
Side-by-side comparison
| Capability | n8n | Make | Zapier |
|---|---|---|---|
| Starting price (paid) | ~$20/month cloud, $0 self-hosted | ~$9/month | ~$20/month |
| Free tier | Unlimited self-hosted; cloud trial | 1,000 ops/month | 100 tasks/month |
| Self-hosting | Yes — first-class, Docker / k8s | No | No |
| Native AI / LLM nodes | Strong — agent, vector store, memory, tool nodes | Good — OpenAI, Anthropic, custom modules | Decent — "AI Actions" + Copilot |
| App catalog | ~500 native + universal HTTP/code | ~2,000+ | ~7,000+ |
| Visual builder | Node graph, JSON expressions | 2D canvas, drag-drop | Linear step list |
| Code support | JavaScript and Python in nodes | JavaScript via custom modules | Limited Code by Zapier |
| Ease of use (non-technical) | Medium — best with some dev background | Medium — friendly canvas | Easy — anyone can ship a Zap |
| Ideal user | Engineering, product, ops with dev support | Ops, growth, agencies | Marketing, sales, founders |
How does pricing actually scale?
Pricing is where most people get this decision wrong. The headline numbers above hide the curve — and the curve is what determines your bill three months in.
Zapier charges per task. Every action in a flow that fires is one task. A simple 3-step Zap that runs 1,000 times a month consumes 3,000 tasks. Plans typically scale roughly like this:
- Free: ~100 tasks/month
- Professional: ~$20/month for 750 tasks, then climbs by tier
- Team: ~$70/month for higher task limits, multi-user
- Enterprise: custom (commonly $1,000+/month for high-volume teams)
Make charges per operation, but each operation is cheaper and the canvas is denser. The same 3-step flow uses fewer ops in many cases. Plans roughly:
- Free: 1,000 ops/month
- Core: ~$9/month for 10,000 ops
- Pro / Teams: ~$16–$29/month for 10,000–100,000 ops
- Enterprise: custom
n8n changes the conversation entirely. Cloud plans are workflow-execution-based (one execution per workflow run, regardless of node count), and the self-hosted version is free forever. Roughly:
- Self-hosted (Community Edition): $0 — pay only for the server you run it on
- Cloud Starter: ~$20/month for 2,500 executions
- Cloud Pro: ~$50/month for 10,000+ executions
- Self-hosted Enterprise: custom — adds SSO, audit logs, RBAC
The takeaway: at low volume Zapier is fine, at medium volume Make is usually the cheapest hosted option, and at high volume self-hosted n8n absolutely crushes both — often by an order of magnitude.
Which one has the best AI features?
This is where the 2026 race is actually being run.
n8n ships with first-class AI agent nodes: an agent node, vector store nodes (Pinecone, Qdrant, Supabase, Postgres pgvector), memory, tool wrappers around any other n8n node, and clean integration with OpenAI, Anthropic, Google, and self-hosted models via Ollama. You can build a full RAG pipeline or a multi-step agent without leaving the canvas. This is the closest thing to LangChain-as-a-visual-tool we have in production.
Make has solid OpenAI and Anthropic modules and a growing list of AI-native templates. It handles "summarize this email, then write to Notion" beautifully. It's weaker on agentic loops and vector stores, where you typically end up wiring third-party services manually.
Zapier has the broadest reach but the shallowest depth. "AI Actions" let you call a model in any step, and Zapier Copilot writes Zaps from natural language. Great for accelerating individual contributors, less suited for agents that need to plan across many steps.
If your roadmap includes building real AI agents — not just "call GPT in step 4" — n8n is in a league of its own. We'll come back to this in the second half of the article.