n8n vs Zapier vs Make: Real AI Agent Costs Compared (2026)

n8n vs Zapier vs Make: The Real Cost of Running AI Agents

TL;DR

Most comparisons judge these tools on features and integrations. Wrong lens. When you're running AI agents, every LLM call, every retry, and every approval step burns a task or operation. At 500k operations per year, self-hosted n8n costs roughly £1,560 while Zapier runs £6,670+. The pricing model is the product decision.

Why This Comparison Exists Now

Here's what happened. In 2023, people used Zapier to connect Gmail to Slack. Five steps. Done. Costs were predictable because workflows were linear.

AI agents aren't linear. They loop.

An AI agent running a ReAct loop — reason, act, observe, repeat — might call an LLM 6–12 times in a single workflow run. Add a retry on failure. Add a human approval step. Add a data enrichment call. One "workflow" is now 15–25 individual operations.

On Zapier, each of those steps is a task. At $19.99/month, you get 750 tasks. Run that agent 50 times and you've burned your monthly allotment in a day.

This is why n8n is blowing up. It's a math story, not a features story.

n8n version 2.10.0 shipped in February 2026 with fixes specifically for AI Agent memory handling and error stability. They're building for this use case. Zapier is still selling to the person who wants to auto-save email attachments to Google Drive.

A Quick History Lesson: We've Seen This Pricing Trap Before

Cloud computing went through the exact same cycle. In the early 2010s, AWS sold cheap compute. Everyone moved workloads to the cloud. Then bills started arriving. The per-request pricing that seemed cheap at demo scale became brutal at production scale.

What happened? Dropbox famously pulled workloads back on-prem and saved millions. The "repatriation" trend came down to one thing: the pricing model didn't match the usage pattern.

The same thing is happening now with automation platforms. Zapier's task-based pricing was fine for linear workflows. It's terrible for AI agents that loop, retry, and branch.

n8n's self-hosted model is the automation version of on-prem. You control the cost. You control the data. You pay for servers, not steps.

1. n8n: Best for AI Agent Workflows and Cost Control

Pricing: Self-hosted is free. Unlimited executions. Zero per-step charges. Cloud starts at $20/month for 2,500 executions. The key distinction: n8n charges per workflow execution, not per node. A 20-step AI agent loop counts as one execution.

Strengths: Native AI Agent node with built-in memory management, tool invocation, and vector store integration. LLM agnostic — connect OpenAI, Anthropic Claude, Google Gemini, or local models like Llama 3 and Mistral from the same node. Advanced error handling with retry and fallback paths. Full data sovereignty on self-hosted. One agency reported managing 700+ ad accounts with a 7-person team running n8n workflows.

Limitations: 400+ integrations versus Zapier's 7,000+. Self-hosting requires Docker knowledge, SSL setup, database management, and monitoring. The learning curve is real. If you don't have someone technical on your team, the first two weeks will be rough.

Best For: Teams running AI agents at volume. Anyone processing sensitive data under GDPR or HIPAA. High-execution workloads where per-task pricing would be ruinous.

2. Zapier: Best for Simple Automations and Non-Technical Teams

Pricing: Starts at $19.99/month for 750 tasks. Every step in a zap counts as a task. A 5-step zap running 150 times burns your monthly limit. Professional plan gets you 2,000 tasks. Enterprise is custom.

Strengths: 7,000+ app integrations. The largest library by far. Dead simple UX — anyone can build a zap in 10 minutes. Reliable uptime. SOC 2 Type II certified. If you need to connect a niche SaaS tool, Zapier probably has it.

Limitations: Cloud-only. No self-hosting. Data processes through AWS US East, which creates compliance friction for anyone handling sensitive data outside the US. Basic retry-only error handling with no fallback routing. The linear step-by-step builder chokes on branching logic. Above 10,000 tasks/month, the bill scales steeply.

Best For: Non-technical teams connecting common SaaS apps. Simple, linear workflows. Monthly task volume under 5,000.

3. Make: Best for Visual Workflow Design and EU Compliance

Pricing: Starts at $9/month for 10,000 operations. Each module execution counts as one operation. Cheaper than Zapier per unit, but AI agent loops still rack up operations fast. SOC 2 Type II certified. Granular data retention controls — you can force execution logs to delete after 24 hours.

Strengths: The visual scenario builder is genuinely good for branching logic. Routers, iterators, and aggregators let you build complex flows without code. EU data centers available. Make's European roots show in its compliance features. About 60% cheaper than Zapier for comparable workloads.

Limitations: Cloud-only. No self-hosting. AI integration happens through HTTP modules and add-on AI nodes, not native agent architecture. You're stitching together API calls, not building an agent graph. No built-in memory management or vector store nodes. At high volume, per-operation pricing still adds up.

Best For: Mid-scale teams that need visual workflow design. EU-based operations with compliance requirements. Teams that find n8n too technical but find Zapier too expensive.

The Cost Math That Actually Matters

Every comparison article shows you the subscription price. Nobody shows you the execution cost for AI agent workloads.

Here's a real scenario. You're running an AI lead enrichment agent. It takes a lead, calls an LLM to research the company, enriches the data via Clearbit, retries on failure, then routes to a human for approval before adding to your CRM.

That's roughly 8 operations per lead. Run it 1,000 times a month. That's 8,000 operations.

On Zapier, that's 8,000 tasks. You need the Team plan at $69/month minimum, and you'll likely overshoot it.

On Make, that's 8,000 operations. The $9/month plan covers 10,000, so you're fine — until next month when volume ticks up.

On n8n self-hosted, that's 1,000 workflow executions. Cost: your server bill. Roughly $20–50/month on a basic VPS.

At 10x that volume — 10,000 leads/month — the gap explodes. Zapier's costs push into hundreds per month. n8n's server bill barely moves.

Syntora published real client numbers: one business saving 15 hours/week through automation, valued at $3,250/month, with $35/month in operating costs on a custom build. That ROI ratio is what you should be targeting.

Most teams pick their automation platform based on the wrong criteria. They compare feature lists and integration counts. The right question is: what does it cost to run my actual workload at 10x scale?

What StoryPros Uses and Why

We use n8n. Not because it's trendy. Because our AI agents run loops, retries, and approval steps at volumes that would bankrupt us on Zapier.

StoryPros builds AI agents that book 30+ meetings a week. That means hundreds of LLM calls per day. Enrichment lookups. Human approval checkpoints. Error retries. On Zapier, each of those steps is a billable event. On n8n self-hosted, we pay for a server.

n8n's January 2026 blog post on human-in-the-loop automation confirmed what we already knew: they're building for AI agent use cases. Wait nodes, approval routing, timeout handling, audit logs. This isn't a bolt-on feature. It's core architecture.

If you're just connecting Salesforce to Slack, use Zapier. Seriously. It's great for that.

If you're building AI agents that prospect, qualify, and book meetings — the kind that run 24/7 and compound over time — the pricing model matters more than the feature list.

FAQ

Is n8n better than Zapier for AI automation?

For AI agent workloads, yes. n8n charges per workflow execution, not per step. An AI agent that loops through 15 nodes counts as one execution on n8n but 15 tasks on Zapier. n8n also has native AI Agent nodes with built-in memory, tool invocation, and support for OpenAI, Anthropic, Gemini, and local LLMs. Zapier doesn't have any of that.

What are the real cost differences between n8n, Zapier, and Make for AI agents?

At 500,000 operations per year, self-hosted n8n costs roughly £1,560 in server expenses. Zapier costs £6,670+ on task-based pricing. Make falls in the middle at about £1,070. The gap widens with volume because n8n's self-hosted model has no per-execution fee — you're paying for infrastructure, not steps.

Is n8n or Make better for AI agent builds?

n8n is better for AI agent builds. It has native AI Agent nodes, memory nodes, vector store nodes, and supports multiple LLMs from the same workflow. Make handles AI through HTTP modules and bolt-on features. n8n also supports self-hosting for full data control, which matters if your agents process customer data. Make is cloud-only with US/EU data center options.

What does self-hosting n8n actually require?

You need a VPS or cloud instance (AWS, DigitalOcean, or similar), Docker for containerized setup, SSL certificates via Let's Encrypt, and a monitoring tool like Uptime Kuma or Grafana. Expect 15–30 minutes for initial setup if you're comfortable with Docker. Budget $20–50/month for a server that handles moderate agent workloads. You're responsible for updates, backups, and uptime, but you get unlimited executions and full data sovereignty in return.

Can I migrate from Zapier to n8n?

There's no one-click migration tool. Complex logic, filters, and data transformations require manual reconstruction. A practical approach: inventory your active zaps, prioritize by volume (highest task consumers first), and rebuild in n8n starting with your most expensive workflows. Most teams see the migration pay for itself within 60–90 days based on reduced per-task billing alone.

Related Reading

• Predictive vs Generative AI: A 2026 Decision Framework
• The Ultimate Guide to AI Agents (StoryPros Edition)