n8n 2.0 vs Zapier vs Make in 2026: Which automation platform wins for AI workflows?
A direct comparison of n8n 2.0, Zapier, and Make (formerly Integromat) for teams building AI-native automation in 2026. Pricing, AI nodes, self-hosting, and real-world limits.
Three years ago, the automation platform debate was simple: Zapier for simplicity, Make for power, n8n for the self-hosting crowd. In 2026, AI-native workflows have scrambled the rankings. Here’s what the comparison actually looks like today.
Why this comparison matters now
The real question is no longer “which tool has the most integrations?” It’s which platform can actually run multi-step AI workflows without breaking the bank or your sanity.
All three platforms have shipped major AI updates in the last 12 months. n8n launched version 2.0 with a rebuilt canvas and native AI agent nodes. Zapier introduced “AI Actions” and a chatbot builder. Make added an AI module layer with direct OpenAI and Anthropic connectors.
The gap has narrowed — but not disappeared.
n8n 2.0: What’s new
n8n’s 2.0 release (late 2025) was the biggest update since the project launched. Key changes:
- New canvas UI — redesigned from scratch, with minimap, sticky notes, and multi-select drag. It finally feels like a professional tool.
- Native AI Agent node — drop in a Claude or GPT model, attach tools (HTTP request, code, sub-workflow), and get an agentic loop out of the box.
- Built-in vector store nodes — Pinecone, Qdrant, and Supabase Vector without custom HTTP calls.
- Improved error handling — execution retry logic, error branches, and better logging.
- n8n Cloud pricing restructure — new “Starter” tier at $20/month for 5,000 executions, with execution-based pricing replacing the old task-based model.
Self-hosting is still fully supported under the fair-code licence. If you run it on a €10/month VPS, the operational cost per workflow execution approaches zero.
Zapier: The safe enterprise choice
Zapier’s strength has always been breadth (7,000+ integrations) and ease of use (non-technical users can build in minutes). That hasn’t changed.
What has changed:
- AI Actions allow GPT-4o calls inline in any Zap, but the UX is still built around linear “if this, then that” logic — not agentic loops.
- Zapier Agents (their new product) attempts agentic workflows, but it’s early and opinionated.
- Pricing remains the steepest: the Professional plan at $49/month includes 2,000 tasks. An AI-heavy workflow that calls Claude 10 times per run will burn through those tasks fast.
Zapier makes sense if: your team is non-technical, you need a specific integration that only Zapier has, or enterprise SLAs matter.
Make: The visual power user’s choice
Make (formerly Integromat) sits in the middle. Better than Zapier for complex branching, cheaper, but lacks n8n’s self-hosting option and AI-native depth.
Current state:
- Scenarios support parallel branches, aggregators, and routers — genuinely more flexible than Zapier Zaps.
- AI modules support OpenAI, Anthropic, and Stability AI natively, but the abstraction is thin — you’re still manually parsing JSON.
- Operations-based pricing: 10,000 ops/month on the Core plan at $9/month. AI calls count as operations, so complex AI workflows can get expensive.
- No self-hosting. You’re on their infrastructure, period.
Make makes sense if: you need visual power without DevOps overhead, your team is technical but doesn’t want to manage servers.
Head-to-head comparison
| n8n 2.0 | Zapier | Make | |
|---|---|---|---|
| AI agent nodes | Native, powerful | Basic (AI Actions) | Moderate |
| Self-hosting | Yes (fair-code) | No | No |
| Pricing entry | $0 (self-hosted) | $0 (limited) | $9/month |
| Pricing at scale | Low (VPS cost) | High | Medium |
| Integrations | 400+ native, unlimited HTTP | 7,000+ | 1,200+ |
| Non-tech friendly | Medium | High | Medium |
| AI workflow depth | High | Low | Medium |
| Error handling | Excellent (v2.0) | Basic | Good |
| Community/OSS | Large, active | Closed | Closed |
Real cost example: a content pipeline
Let’s say you run a workflow that:
- Triggers every hour
- Fetches 5 RSS items
- Calls Claude for each to classify and summarise (5 LLM calls)
- Stores results in a database
That’s roughly 120 runs/day × 5 LLM calls = 600 operations/day.
| Platform | Monthly ops | Monthly cost (platform only) |
|---|---|---|
| n8n (self-hosted, €10 VPS) | Unlimited | ~€10 |
| n8n Cloud Starter | 5,000 | $20 (would need Pro) |
| Make Core | 10,000 | $9 (maxed in ~16 days) |
| Zapier Pro | 2,000 | $49 (exhausted in 3 days) |
The LLM API costs (Claude Haiku at ~$0.001/call) are roughly $18/month on top regardless of platform.
Self-hosted n8n wins on cost at this volume, and it’s not close.
Who should use what
Choose n8n if:
- You’re building AI-native workflows with LLMs, vector stores, or agent loops
- Cost at scale matters and you’re comfortable with a VPS
- You want to own your infrastructure and data
- You need custom nodes or complex branching logic
Choose Zapier if:
- You need a specific integration that only Zapier covers
- Your team is non-technical and needs to maintain workflows
- Enterprise procurement, SSO, or audit logs are required
- You’re building simple linear automations (less than 100/day)
Choose Make if:
- You want visual power without server management
- Your workflow volume is under 10,000 ops/month
- The specific integrations you need exist in Make’s library
Our setup at Mimir Lab
We run n8n self-hosted on a Hetzner VPS (CX21, €5.77/month). Every AI workflow in the lab runs through it — from the Gmail classifier to the Mimir Command Center. Total infrastructure cost: under €30/month including the VPS, domain, and API costs.
If we ran the same workflows on Zapier, we’d pay north of €200/month in platform fees alone.
The n8n 2.0 canvas update solved the last real UX complaint we had. It’s our unconditional recommendation for anyone serious about AI automation.
All prices as of Q1 2026. Check platform sites for current pricing.