Most comparison articles hand you a feature matrix. Feature matrices are close to useless here, because in 2026 all three platforms do roughly the same things: all three added serious AI in the last year, all three handle branching, all three connect to everything you use.
So here is the comparison that actually changes a decision: what happens to your bill as you grow.
The billing unit: the only thing that really matters
Take one workflow. It has 8 steps. It runs 10,000 times a month. That is a completely ordinary mid-complexity automation: a lead comes in, gets enriched, scored, routed, logged, and announced in Slack.
| Platform | Counts | Units consumed | Roughly costs |
|---|---|---|---|
| Zapier | Each action step = 1 task | 80,000 tasks | $250 - $400+/mo |
| Make | Each module run = 1 operation | 80,000 operations | $150 - $200/mo |
| n8n Cloud | Each workflow run = 1 execution | 10,000 executions | about $50/mo |
| n8n self-hosted | Nothing. It is your server. | Unlimited | $5 - $50/mo (the VPS) |
Same work. Same result. A 5-8x spread, and it widens with every step you add to the workflow.
That is the whole article, really. Everything else is detail.
Why it happens: add a ninth step to that workflow and Zapier's bill goes up 12.5%. Make's does too. n8n's does not move at all, because it is still one execution. Zapier and Make price complexity. n8n prices frequency. So the question is not "which is cheapest," it is "is my automation wide, or is it busy?"
- Wide (many steps, run rarely) means n8n's model is dramatically cheaper
- Busy (few steps, run constantly) means the gap narrows a lot
- Both means n8n, and it is not close
The entry prices, honestly
| Platform | Entry | What you get | Free tier |
|---|---|---|---|
| Zapier | about $19.99/mo (annual, Professional) | 750 tasks | Basic 2-step Zaps |
| Make | about $9/mo | 10,000 credits | Yes |
| n8n Cloud | about 20 euros/mo annual, 24 monthly | 2,500 executions, unlimited users | No |
| n8n self-hosted | $0 licence | Unlimited executions | Community Edition |
Pricing verified July 2026. All three vendors change plans and allowances often, so re-check the current rates before you commit to anything. n8n publishes in euros; euro figures below are converted at roughly 1.10 USD.
Look at Zapier's entry row again. 750 tasks for $19.99. A two-step workflow processing 100 records consumes 200 tasks. You can exhaust a month's allowance in an afternoon.
Make gives you 10,000 credits for $9, roughly 10x more allowance for half the price. That comparison alone should be in every honest article about this and almost never is, because Zapier has the affiliate programme.
And n8n self-hosted: the Community Edition is free software with unlimited executions. You pay for the server, typically $5 to $20 a month on a basic VPS. Note the trade. You are not saving money, you are converting a subscription into a maintenance obligation. Someone has to secure and update that box. If that someone does not exist, the free tier is not free, it is a liability with a countdown.
The crossover: where it flips
The threshold everyone talks about is 10,000 tasks a month, but that is imprecise because it ignores step count. Here is the real geometry:
| Your situation | Cheapest | Notes |
|---|---|---|
| Under about 1,000 tasks/mo, simple workflows | Zapier | Genuinely. The premium is small and the UX is worth it. |
| 1,000 to 5,000 tasks/mo | Zapier or Make | Make is cheaper, Zapier is easier. Pick your constraint. |
| 5,000 to 10,000 tasks/mo | Make | Zapier's bill starts scaling badly here. |
| Over 10,000 tasks/mo | n8n | Make is 70-80% cheaper than Zapier; self-hosted n8n is about 95% cheaper. |
| Any volume, 8+ steps per run | n8n | The execution model crushes it. |
| AI agents with memory and tools | n8n | Not close. See below. |
| Data residency or compliance | n8n self-hosted | The only one of the three that can be. |
| Nobody technical on the team | Zapier | The cheapest tool you cannot operate costs infinity. |
The most honest sentence in this article: if you run a handful of simple Zaps, stay on Zapier. The migration will cost you more in time than you will save in licence fees, and you will spend it on a platform your team cannot maintain. That is our automation position and we mean it.
The AI question, which is now the real question
All three shipped AI in the last year, and the marketing makes them sound equivalent. They are not.
| Zapier | Make | n8n | |
|---|---|---|---|
| AI in 2026 | Zapier Agents, AI Copilot builds Zaps from natural language | Maia AI assistant, Make AI Agents | n8n 2.0: native LangChain, 70+ AI nodes, vector DB connectors, persistent agent memory, self-hosted LLM support |
| Best for | "Summarise this email, post to Slack" | Mid-complexity AI steps | Real agents: memory across runs, tool calls, RAG |
| AI pricing | Within the task model | Within the credit model | Same execution pricing, no separate AI tier |
That last cell matters more than it looks. If you are building an agent that keeps memory across runs, calls tools, and queries a vector store, n8n is the pick and it is not close, and the AI work does not sit on a separate, more expensive meter.
If you want a simple agent a marketer can manage without help, Zapier's is friendlier. Both statements are true. Pick by who is operating it.
The four costs the pricing pages do not mention
1. The maintenance obligation (self-hosted n8n). Server, updates, security, backups. Realistically 2 to 4 hours a month once stable, and a bad afternoon when it is not. At a loaded ops rate that is $150 to $400 a month of attention, which for many teams erases the saving entirely versus Make. Be honest about whether you are saving money or moving it into a column you do not measure. It is also the reason workflows break in production rather than in testing.
2. Integration depth, not count. Zapier has 8,000 or more integrations, Make roughly 1,500 to 2,000, n8n fewer pre-built but full HTTP and code. The headline count misleads, because many integrations across all platforms cover only the basic functions of a service. The right question is not "does it connect to HubSpot," it is "does it connect to the part of HubSpot I need," and that is a five-minute check that saves a five-week discovery.
3. Migration. Most workflows port in 1 to 3 days each. Total time scales with count, not complexity, so a 30-Zap account is typically 1 to 2 weeks of focused work. Budget it honestly before you switch.
4. The rebuild-on-exit risk. Zapier and Make are cloud-only. Your logic lives in their UI. n8n workflows are exportable JSON in your own instance, which is why we standardised on it: any competent operator can pick them up, including one who is not us.
The test that beats every comparison article
Before you migrate anything:
- Take your busiest workflow. Count its steps. Count its monthly runs. Multiply. That is your Zapier task consumption, usually 5 to 10 times what people guess.
- Use Zapier's 14-day Professional trial to measure real task consumption instead of estimating it. Teams consistently under-guess.
- Ask who is on call. If the honest answer is "nobody," self-hosted n8n is a trap regardless of the maths.
- Then decide. If your number is under 5,000 tasks and nobody is technical, you have your answer and it costs $20 a month.
Our position, stated plainly
We standardised on n8n after building on all of them, and we will tell you why in the same breath as when not to.
Why we chose it: self-hostable, so data stays on your infrastructure, which is a hard requirement for many compliance teams and impossible with cloud-only tools. Flat-cost at scale, because per-task pricing punishes success. Over 1,000 integrations plus real JavaScript or Python when a connector does not exist. AI-native, with agent nodes inside the workflow rather than bolted on via a third tool. And no lock-in to us either: exportable JSON, in your instance, documented.
When we would tell you to stay put: you run under 5,000 tasks a month, your workflows are simple, and nobody on your team wants to think about a server. Then Zapier is correct, and anyone telling you otherwise is selling migration work.
That is, unavoidably, the honest position of a company that sells migration work. Which is exactly why we have published the numbers instead of the conclusion.
Bring us your current automation bill and your three most annoying manual processes. We will audit what you are running and give you the honest number, including "stay where you are" if that is the answer.
Frequently asked questions
Usually, and often dramatically. For a 10,000-run per month workflow with 8 steps: n8n Cloud costs about $50 a month against $250 to $400 or more on Zapier. Self-hosted n8n is roughly 95% cheaper for identical workloads. Under about 5,000 tasks a month the gap is small enough that Zapier's ease of use is worth the premium.
A Zapier task is one action step. A Make operation is one module run. An n8n execution is one full workflow run regardless of step count. An 8-step workflow running once costs 8 tasks, 8 operations, or 1 execution.
The self-hosted Community Edition is free software with unlimited executions. You pay for the server, typically $5 to $20 a month, and for the time to secure, update and back it up. n8n Cloud starts around 20 euros a month and removes that obligation.
Not automatically. It pays off when task volume makes per-task pricing painful, when you need AI agents or custom code, or when data residency matters. If you run a few simple Zaps, stay. Migration typically takes 1 to 3 days per workflow.
n8n, if the agent is real: native LangChain, 70+ AI nodes, vector database connectors, persistent memory and human-in-the-loop patterns, all on the same execution pricing with no separate AI tier. Zapier's AI is friendlier for simple, marketer-managed agents.
Zapier, with 8,000 or more, then Make at roughly 1,500 to 2,000, then n8n. But integration depth varies across all three, and n8n's HTTP and code nodes reach anything with an API. Check the specific endpoint you need, not the headline number.
No. Both are cloud-only. n8n is the only one of the three that supports self-hosted deployment, which is what makes strict data-residency and compliance requirements achievable.
