n8n vs Make — pricing, executions vs credits, and self-host TCO

Compare n8n vs Make on one normalized workload. Model credits, executions, retry overhead, VPS and maintenance before choosing cloud or self-host.

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Cost at 100 / 500 / 2,000 workflow runs

Scenario model: 3 billable actions/modules per workflow run, with no retry overhead. Zapier tasks and Make credits are runs × actions; n8n Cloud uses workflow executions. Values above the largest verified tier are left unpriced, not extrapolated. Use the calculator to change the workload. Prices verified from vendor pages in our pricing index.

3-year TCO (at 500 workflow runs/mo)

Make saves about $504 over 3 years at this volume (list price only).

Scenario model: 3 billable actions/modules per workflow run, with no retry overhead. Zapier tasks and Make credits are runs × actions; n8n Cloud uses workflow executions. Values above the largest verified tier are left unpriced, not extrapolated. Use the calculator to change the workload.

At a glance

Winner by use case

• Tightest budget: Make — entry plan is $14/mo cheaper ($168/year at entry tier).
• Fastest to learn: n8n (3.8/5 ease of use).
• Most capability: n8n (4.7/5 feature depth).
• Best value overall: n8n (4.8/5 value score).

Feature matrix

Pricing, side by side

Strengths and weaknesses

Our verdict

Feature lists do not settle n8n vs Make. Both can build multi-step workflows, call APIs and connect common business apps. The decision is about workload shape, operating ownership and the unit that becomes your bill.

Use the workload lab above first. It converts the same monthly runs into Make credits and n8n executions, then keeps VPS and maintenance visible for self-hosting. If your workload exceeds the largest published tier stored by StackPick, the result says “check vendor” instead of multiplying price linearly.

The billing unit changes the answer

• Make: standard module runs generally consume credits. A workflow with five billable modules that runs 1,000 times needs about 5,000 credits before retry or iterator overhead. Some AI features may use variable credits.
• n8n Cloud: pricing is based on workflow executions. A five-node and a fifty-node workflow can each count as one execution, although retries, sub-workflows and execution mode still matter.
• n8n self-host: Community software removes the Cloud execution fee, not the cost of hosting and operating it.

This is why a table comparing “10,000 credits” with “10,000 executions” is not useful. StackPick's static tables use one normalized scenario, and the interactive lab lets you change its assumptions.

Cloud vs self-host: the cost n8n moves to you

Self-hosting can reduce vendor spend, but it transfers work:

1. container and database upgrades;
2. encrypted credentials and secrets management;
3. backups and restore tests;
4. monitoring, alerting and log retention;
5. incident response and capacity planning;
6. security patches and access control.

Enter a realistic VPS bill, maintenance hours and labor value in the lab. If your team already runs this infrastructure, incremental cost may be low. If nobody owns it, a cheap server is not the full TCO.

Three scenarios where the winner changes

A small marketing team with short workflows

Example: lead form → CRM → confirmation email. Make usually provides a low-cost visual cloud path; n8n Cloud may be unnecessary if the team does not need code or self-hosting. Make also has the active affiliate route in this comparison, but that does not change the model or verdict.

A technical team with long or AI-heavy workflows

Example: ingest → enrich → branch → LLM → validate → database → notification. n8n's execution model can become attractive because every node is not billed as a separate task. Code nodes, AI agent patterns and self-host data control strengthen the fit.

An operations team that cannot own infrastructure

n8n Community may look cheapest in software cost, but a team with no on-call owner should compare n8n Cloud with Make Cloud. Reliability ownership can outweigh the monthly plan delta.

AI workflows

n8n exposes AI agent, model and vector-store patterns directly in the workflow builder and allows code alongside visual nodes. Make offers AI modules and an AI-assisted scenario experience. The practical question is not which has the longer AI feature list; it is whether your workflow needs code/control or a simpler visual cloud handoff.

Model external AI-provider spend separately. LLM, transcription and vector-database charges are not included in either platform plan here.

Debugging, collaboration and governance

Make's visual canvas is easier for many marketing and operations users to follow. Its Pro tier in the StackPick dataset adds priority execution, custom variables and full-text logs. n8n is more natural for technical operators who are comfortable with expressions, JSON and code.

For regulated or larger teams, verify SSO, audit logs, environment separation, credential controls, support and data residency at the current vendor source. These requirements can force a higher plan even when a lower tier covers volume.

Migration risk

Do not migrate only because one monthly estimate is lower. Add:

• workflow inventory and dependency mapping;
• rebuild and test hours;
• dual-running during cutover;
• rollback and data-reconciliation time;
• retraining for operators;
• the cost of integrations that need custom API work.

A $20 monthly saving can be negative ROI if the migration consumes a week. Use the workflow automation cost calculator for recurring cost, then add project labor separately.

What StackPick verified — and what it did not

StackPick verified the stored public tier prices, billing descriptions, capacities and dates from vendor pricing sources. The workload conversion and TCO are reproducible calculations. We have not claimed a universal uptime, support-quality or latency winner because this page does not contain a controlled production benchmark.

That evidence boundary is deliberate: a documented limitation is more useful than a made-up hands-on test.

Verdict

Choose Make when a non-developer team wants a visual cloud platform, your workflows stay inside a published credit tier and low operating overhead matters most.

Choose n8n Cloud when workflows are long, AI/code-heavy or execution pricing better matches the workload, but you still want the vendor to operate the service.

Choose n8n self-host only when data/control requirements justify it and someone explicitly owns upgrades, backups, monitoring and incidents.

If your intent is building a service or selling templates rather than buying a platform, use the separate how to make money with n8n guide. Keeping that intent separate prevents this buying comparison from drifting into an income article.

Pricing sources

• n8n pricing — tool record verified 2026-08-25
• Make pricing — tool record verified 2026-08-25

FAQ

Is Make cheaper than n8n?

Yes. Make starts at $9/mo versus $23/mo for n8n (per month, 10,000 credits, billed annually). Over a year that is a $168 difference at entry tier.

Which is easier to use, n8n or Make?

Based on our scoring, n8n is easier to get started with (ease-of-use 3.8/5 vs 3.7/5).

Which has more features, n8n or Make?

n8n scores higher on feature depth (4.7/5). Key differentiators: Executions-based pricing: one execution = whole workflow run, any number of steps; 500+ integrations plus HTTP request node for anything else; Code nodes (JavaScript/Python) inside visual flows.

What is the 3-year TCO of n8n vs Make?

At ~500 units/mo on verified tiers, n8n is about $828 over 3 years ($23/mo) versus Make at $324 ($9/mo). Make saves roughly $504 across 3 years before add-ons. Scenario model: 3 billable actions/modules per workflow run, with no retry overhead. Zapier tasks and Make credits are runs × actions; n8n Cloud uses workflow executions. Values above the largest verified tier are left unpriced, not extrapolated. Use the calculator to change the workload.

Full reviews: n8n review · Make review

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