Make vs n8n vs Zapier (2026)
Three tools, three very different philosophies. Make gives you a visual canvas and strong value. n8n gives you complete control and a free self-hosted option. Zapier gives you the easiest path to 7,000+ integrations. Here's how to choose.
- You want the best price-to-power ratio
- Visual workflows matter to your team
- You're not technical but want real depth
- You can self-host (or have a developer)
- You need code nodes or maximum flexibility
- Data privacy or compliance is a concern
Quick verdict
Make wins on value. For most non-technical teams, Make's visual canvas, generous operation limits, and $9/month entry point make it the clear first choice. It does almost everything Zapier does at a fraction of the price.
n8n wins on flexibility and cost at scale. Self-hosted n8n is free with unlimited executions. For technical teams, the code-node capability and AI agent depth are unmatched. Cloud n8n at $24/month for 2,500 executions is less compelling - the self-hosted path is where the value is.
Zapier wins on integrations and ease. 7,000+ apps, the most polished onboarding experience, and the best AI features for non-technical users. The right choice when you need a specific integration that others don't support, or when setup friction matters more than price.
Pricing comparison
| Plan | Make | n8n | Zapier |
|---|---|---|---|
| Free | 1,000 ops/mo, 2 scenarios, 15-min interval | Unlimited (self-host) / 14-day trial (cloud) | 100 tasks/mo, single-step only, 15-min interval |
| Entry paid | $9/mo - 10,000 ops, unlimited scenarios | $24/mo cloud (2,500 exec) / $5-7/mo VPS self-host | $20/mo annual (750 tasks, multi-step) |
| Mid tier | $16/mo - 10,000 ops + priority execution | $60/mo - 10,000 executions | $49/mo - 2,000 tasks, 1-min polling, webhooks |
| Team tier | $29/mo - team roles + shared scenarios | Custom enterprise | $69/mo - shared workspace, SSO |
| Annual discount | ~15% off | 17% off cloud | ~30-40% off |
Prices as of June 2026. Always verify on the provider's site before purchasing.
Pricing in practice
The credit/task counting differences matter at scale. Make counts every operation in a scenario (each trigger, router, filter, and action step). A 5-step workflow run once uses 5 Make credits. Zapier counts successful action steps - the same workflow would use 4 Zapier tasks (the trigger is free). At 1,000 workflow runs per month with a 5-step average, you'd use roughly 5,000 Make operations vs 4,000 Zapier tasks. Make's $9 Core plan covers this comfortably. Zapier's $49 Professional plan (2,000 tasks) does not.
n8n's execution model is simpler: one execution = one workflow run, regardless of how many steps it has. The self-hosted Community Edition has no execution limits, making it the clear winner for high-volume use cases where you have someone who can manage a VPS.
Features head-to-head
| Feature | Make | n8n | Zapier |
|---|---|---|---|
| Interface | Visual canvas (best-in-class) | Node-based canvas | Linear list builder |
| App integrations | 1,500+ | 400+ native + HTTP extensible | 7,000+ (largest) |
| Conditional logic | Routers, filters, iterators | IF node, switch, merge | Paths (paid), filters |
| Error handling | Dedicated error routes | Try/catch nodes | Basic (paid tiers only) |
| Code nodes | No (HTTP calls only) | Yes (JS + Python) | No (basic formatter only) |
| Self-hosting | No | Yes (Community Edition free) | No |
| Webhooks | All paid plans | All plans | Professional+ only |
| Scheduling | 1-min minimum (paid) | Cron expressions | 1-min minimum (Professional) |
| Version history | Scenario versioning | Workflow version history | Version history (Team+) |
AI capabilities
All three tools now treat AI as a first-class workflow step, but they've taken different approaches.
Make: AI via HTTP steps
Make integrates with AI through its HTTP module or via dedicated OpenAI, Anthropic, and Perplexity modules. You can call any LLM API, pass in dynamic variables from earlier workflow steps, and use the response to route decisions or enrich data. It's flexible but requires manual setup - there's no pre-built "AI agent" node. Works well for: content classification, data extraction from unstructured text, summarization, and generating dynamic content in automated emails.
n8n: native AI agent architecture
n8n has the deepest AI integration. Its AI Agent node is built on LangChain concepts and supports tool calling, memory (in-workflow or via vector stores), and multi-step reasoning. You can give an agent access to tools (email, database, HTTP) and let it decide which to call. The AI sub-nodes (OpenAI, Anthropic, Ollama for local models) are first-class citizens. For teams building genuine AI workflows - not just "call GPT mid-zap" - n8n is the better foundation.
Zapier: AI for non-technical users
Zapier's AI is the most accessible. Natural language workflow generation ("describe what you want and Zapier builds the Zap") lowers the setup barrier significantly. Zapier AI steps support OpenAI and Anthropic models and can be dropped into any Zap. Zapier also offers Zapier Chatbots (build a chatbot powered by your Zaps) and Zapier Agents (multi-step reasoning with tool access). These features are polished but less flexible than n8n's agent nodes.
| AI feature | Make | n8n | Zapier |
|---|---|---|---|
| LLM integration | Via HTTP / dedicated modules | Native AI nodes (LangChain-based) | Zapier AI steps |
| AI agents | Manual via HTTP chains | Dedicated AI Agent node with tools | Zapier Agents (beta) |
| Memory support | Manual (store in database) | Built-in + vector store nodes | Limited |
| Local models | Via HTTP (Ollama) | Native Ollama node | No |
| Natural language setup | No | No | Yes (describe your Zap) |
Decision guide: which one to choose
- You're a non-technical user who wants real workflow depth without code
- You're migrating from Zapier and want lower costs
- You need visual debugging - seeing the whole workflow at once
- Your team will share and maintain workflows collaboratively
- Budget matters and you need 10,000+ operations per month
- You can self-host (or have a developer who can)
- Data privacy or GDPR compliance is a concern
- You need code-level control (JavaScript or Python in workflows)
- You're building serious AI agent workflows, not just "call GPT"
- High execution volume makes per-task pricing unsustainable
- You need a specific integration that only Zapier supports (check their 7,000+ app list)
- Your team has zero technical appetite and needs the smoothest onboarding
- You want natural language workflow generation to get started fast
- Low volume (under 750 tasks/month) makes the Starter plan viable
- You're already paying for Zapier and the switch cost outweighs the savings
Frequently asked questions
Is Make cheaper than Zapier?
Yes, significantly. Make's Core plan starts at $9/month for 10,000 operations. Zapier's Starter plan starts at $20/month (annual) for 750 tasks. At comparable usage levels, Make is typically 3-5x cheaper. The counting methods differ - Make counts each step in a workflow, Zapier counts successful action steps - but the cost difference is real regardless.
Can n8n replace Zapier?
For technical users, yes - n8n's self-hosted Community Edition covers most Zapier use cases for free. n8n has fewer native integrations (400+ vs Zapier's 7,000+), but HTTP request nodes and a growing community library fill most gaps. Non-technical users will find n8n harder to start with.
Which is best for AI workflows?
n8n has the deepest native AI integration with dedicated LangChain-based AI agent nodes, memory management, and vector store support. Make supports AI via HTTP calls to any LLM API. Zapier has the most user-friendly AI features (natural language workflow creation) but less flexibility for advanced AI use cases. For serious AI agent workflows, n8n is the strongest foundation.
Should I switch from Zapier to Make?
If you're paying more than $30/month for Zapier and your workflows don't depend on a Zapier-exclusive integration, the switch is almost always worth it financially. Make's visual canvas is also a meaningful upgrade over Zapier's linear step format. The main switching cost is rebuilding existing Zaps in Make's interface (typically a few hours per workflow). See our full automation tools ranking for more context.
Pricing and features as of June 2026 - always check the provider's site. Also see: Best AI Automation Tools and Best No-Code AI Agent Builders.