Automation platform cost
Zapier vs Make vs n8n AI Workflow Cost
Compare AI workflow automation cost across Zapier tasks, Make credits, n8n executions, AI/API calls, platform subscriptions, retries, hosting, monitoring, support hours, and client margin.
The comparison rule
Do not compare Zapier, Make, and n8n only by subscription price. Compare them by cost per completed business run: one qualified lead, one triaged support ticket, one synced order, one generated report, or one completed back-office workflow.
A run can consume multiple Zapier tasks, multiple Make credits, or one n8n workflow execution. Then add AI calls, retries, data providers, hosting, monitoring, and support time.
The practical formula
Monthly workflow cost equals billable platform units plus AI/API usage, subscriptions, hosting, failure buffer, and support labor. For an agency, the quote also needs payment fees and target margin.
Use the AI Workflow Cost Calculator to test the same workflow under different task, credit, or execution assumptions.
Billing models to normalize
The core difference is not just price. Each platform meters a different thing, so the same business workflow can produce very different invoices.
| Platform | Billing unit | How it scales | Best fit |
|---|---|---|---|
| Zapier | Tasks | A multi-step Zap can consume multiple tasks per completed business run. | Simple automations, broad app coverage, and teams that value setup speed. |
| Make | Credits | Each module action in a scenario usually counts as one credit, so branches and repeated modules change cost. | Visual workflows, branching logic, and high-volume operations that need detailed control. |
| n8n | Workflow executions | Cloud pricing is based on completed workflow executions rather than the number of steps inside each execution. | Technical teams, internal tools, custom logic, and workflows where step count would otherwise be expensive. |
Inputs that change the winner
A platform that looks cheap for one simple trigger can become expensive when the workflow branches, calls an AI model repeatedly, retries failed rows, or needs monthly maintenance.
| Input | Why it matters |
|---|---|
| Completed business runs | Use the business event as the common denominator: lead enriched, ticket triaged, invoice processed, or report generated. |
| Billable units per run | Convert Zapier tasks, Make credits, or n8n executions into the same per-run model. |
| AI and external API calls | LLM calls, embeddings, search, scraping, email, CRM, and enrichment APIs often exceed the automation platform fee. |
| Failure and retry buffer | Bad input data, rate limits, webhook retries, and broken credentials increase real monthly usage. |
| Monitoring and support | Even low-code workflows need logs, fixes, credential refreshes, API changes, and client reporting. |
Count tasks per run
Good for simple SaaS workflows, but multi-step AI automations need task planning.
Count credits per scenario
Good for visual branching and operations-heavy workflows when credits are estimated carefully.
Count executions and ownership
Good for technical teams, but hosting, updates, logs, and support still belong in the cost model.
Which platform fits the workflow?
| Situation | Likely fit |
|---|---|
| Need the fastest path across many SaaS apps | Zapier usually wins on connector breadth and non-technical setup speed. |
| Need visual branching, transforms, and higher-volume scenarios | Make often gives operators more control over flow shape and unit usage. |
| Need custom code, self-hosting options, or step-heavy workflows | n8n can be stronger when the team can maintain the workflow stack. |
| Need client-facing agency margin | Choose the platform after calculating support hours, retries, subscriptions, and target margin. |
Common cost mistakes
| Mistake | Better approach |
|---|---|
| Comparing only monthly subscription prices | Normalize every plan into cost per completed business run. |
| Counting a workflow run as one unit on every platform | Zapier, Make, and n8n bill different units. Convert tasks, credits, and executions first. |
| Ignoring AI usage inside the workflow | Add model calls, prompt words, retries, tool calls, and data providers separately. |
| Forgetting operational ownership | Budget monitoring, broken workflows, API changes, and security updates, especially for self-hosted setups. |
Related calculators and guides
Sources to verify
Platform pricing and billing rules change. Check official pricing pages before quoting a client or choosing a production automation stack.