Make vs n8n: The Complete 2026 Workflow Automation Comparison
Per-operation billing, per-execution billing, self-hosting, and the buyer-side tradeoffs that decide which tool actually saves you money.
Make vs n8n comes down to one core question: do you want a polished cloud-only visual builder billed per operation, or an open-source platform you can self-host and run per execution? Both are stronger value than Zapier for most workflows, but they fit very different teams.
Make charges credits for every module step that processes data — most modules consume one credit each. n8n charges per workflow execution regardless of how many steps run inside it. That single difference reshapes the price curve as your volume grows.
n8n is open source under the Sustainable Use License and can be self-hosted on a $20/month VPS. Make is closed-source SaaS only. That difference also reshapes data residency, AI-node flexibility, and how much engineering help you need.
This guide compares Make.com and n8n on the dimensions buyers actually care about in 2026 — pricing math at real volumes, free tiers, self-hosting, AI nodes, integration counts, branching and loops, code support, and the learning curve.
Make (Make.com) vs. n8n: Side-by-Side
| Dimension | Make (Make.com) | n8n |
|---|---|---|
| Pricing model | Per operation (credit per module step) | Per workflow execution (full run = 1 execution) |
| Starting paid plan | Core at roughly $9–$10.59/mo for 10,000 ops | Starter cloud at roughly $20/mo for 2,500 executions |
| Free tier | 1,000 operations/month, indefinite | Self-hosted Community Edition free; cloud has 14-day trial |
| Self-hosting | No — cloud only | Yes — Docker, Kubernetes, or VPS |
| Open source | No | Yes (Sustainable Use License, fair-code) |
| AI nodes | OpenAI, Anthropic, and built-in AI agents in the visual builder | Native LangChain nodes, custom AI agents, any model via HTTP |
| Pre-built integrations | Roughly 2,000+ apps | Roughly 500+ native nodes plus universal HTTP request node |
| Branching and loops | Routers, filters, iterators, aggregators — visual | IF, Switch, Loop nodes plus arbitrary code branching |
| JavaScript / code support | Limited — JSON parsing and basic functions | Full JavaScript and Python in Code node |
| Learning curve | Gentle — drag-and-drop visual scenarios | Steeper — node-graph UI rewards technical users |
| Data residency | EU or US region selectable on cloud | Anywhere you host — full sovereignty when self-hosted |
| Best for | Non-technical operators wiring SaaS together fast | Technical teams running high-volume or data-sensitive flows |
Quick Verdict: Make vs n8n
Pick Make if you want the fastest path from idea to working workflow with no servers to manage. Pick n8n if you want lower per-execution cost at scale, self-hosting, or full code flexibility inside your flows.
Make wins on time-to-first-workflow. Its visual scenario builder is the easiest in the category, the free tier gives you 1,000 operations per month forever, and the $9 Core plan covers most small business use cases.
n8n wins on unit economics above roughly 80,000–100,000 operations per month, on data residency, and on any workflow that needs custom JavaScript, Python, or a model the visual catalog does not include.
For Layer3 Labs clients in legal, healthcare, financial services, and other regulated verticals, the self-hosting question often decides this on its own — n8n on your own infrastructure keeps client data inside your control plane.
Not sure whether Make or n8n is the right call for your business? Book a free consultation and we'll map an unbiased recommendation against your actual workflows and integration stack.
Book a ConsultationMake vs n8n Pricing: Per Operation vs Per Execution
The pricing models are fundamentally different and that difference matters more than the headline price. Make bills per operation — every module step in a scenario consumes a credit. n8n bills per execution — one full workflow run counts as one execution no matter how many steps run inside it.
Make Core starts at roughly $9–$10.59/month for 10,000 operations. Pro is around $16/month, Teams around $29/month, and Enterprise is custom. As of November 2025, Make moved fully to credits and charges 25% more for top-up operation packs than for the credits included in your plan.
n8n Cloud Starter begins around $20/month for 2,500 executions. A 20-step workflow that runs 2,500 times costs the same as a 3-step workflow that runs 2,500 times. On Make, that 20-step workflow would burn through credits 20x faster.
The crossover point matters. For low-step, high-frequency flows, Make is often cheaper. For multi-step ETL, scraping, or AI pipelines, n8n is dramatically cheaper because step count is free. Above 80,000–100,000 operations per month consistently, n8n self-hosted on a $20 VPS typically pays back its setup time within three months versus Make Core plus operation packs at ~$109/month.
- Make Core: ~$9–$10.59/mo, 10,000 operations
- Make Pro: ~$16/mo, 10,000 operations plus higher data limits
- n8n Cloud Starter: ~$20/mo, 2,500 executions
- n8n self-hosted: ~$20/mo VPS, unlimited executions
- Make free tier: 1,000 operations/month indefinitely
- n8n free tier: Community Edition self-hosted, free forever
Self-Hosting: The Make vs n8n Dealbreaker
n8n can be self-hosted; Make cannot. This single fact decides the choice for many regulated businesses.
n8n ships as a Docker container, Helm chart, or npm package. You can run it on a $20/month VPS, an on-prem server, or inside your own AWS, GCP, or Azure account. Your customer data, API keys, and workflow logs never leave your infrastructure.
Make is cloud-only. You choose between an EU or US region on the Make.com platform, but the data passes through Make-controlled infrastructure. That is fine for most marketing automations and fine for many SMBs, but it is a hard stop for some HIPAA workflows, attorney-client privileged data, or contractually data-resident customer information.
Self-hosting is not free, though. You own uptime, version upgrades, backups, and scaling. For a 1–10 person SMB without engineering staff, n8n Cloud or Make is usually the right call. For a firm with technical staff or a managed-services partner like Layer3 Labs, self-hosted n8n typically costs less and offers more control over sensitive client data.
- n8n self-hosted: Docker, Kubernetes, VPS, or on-prem
- Make: cloud only, EU or US region selectable
- Data sovereignty: n8n self-hosted keeps records inside your perimeter
- Operational burden: self-hosting means owning uptime and upgrades
AI Nodes and Agent Workflows
Both tools have strong native AI support in 2026, but n8n is more open-ended and Make is faster to wire up. Make ships AI agents, OpenAI, Anthropic, and many vertical AI modules inside its visual builder. n8n ships native LangChain nodes, Code nodes for any Python or JavaScript AI library, and HTTP nodes for any model API.
For a non-technical operator building a "summarize this email and post to Slack" flow, Make is the faster route. The AI agent module is drag-and-drop and the cost is predictable.
For multi-step AI agents — retrieval, tool use, branching reasoning, custom embeddings — n8n is more flexible. You can drop a LangChain agent into a workflow, branch on its output with JavaScript, and swap models per branch.
A practical Layer3 detail: token costs in either tool are pass-through to OpenAI, Anthropic, or your model provider. The workflow tool is just the orchestrator. n8n self-hosted lets you keep prompts and outputs entirely inside your infrastructure, which matters for any AI workflow handling regulated client data.
- Make: AI agents, OpenAI, Anthropic, Mistral built into visual builder
- n8n: native LangChain nodes plus Code node for any model
- Custom embeddings, vector DB writes: easier in n8n
- Drag-and-drop AI for one-step prompts: easier in Make
Integrations, Branching, and Code Support
Make has more pre-built integrations; n8n has more flexibility per integration. Make ships roughly 2,000+ pre-built app integrations. n8n ships roughly 500+ native nodes plus a universal HTTP Request node that connects to any REST API.
For mainstream SaaS — HubSpot, Salesforce, Google Workspace, Stripe, Slack — both tools cover the basics. Make often has deeper trigger and action coverage for popular apps because they have been at it longer.
Branching and loops are where n8n pulls ahead for complex flows. Both tools support routing, conditional logic, and iteration. But n8n adds a Code node where you can write JavaScript or Python directly inside the workflow — useful for data transformations, custom logic, or calling internal services. Make is limited to JSON parsing and the functions exposed in its module library.
For workflows that mostly chain SaaS apps together, Make is faster. For workflows that touch a custom database, an internal API, or need data transformation that the visual builder cannot express, n8n is the better fit.
- Make: ~2,000+ pre-built integrations, often deeper per app
- n8n: ~500+ native nodes plus universal HTTP for any REST API
- n8n Code node: full JavaScript or Python inside any workflow
- Make: JSON parsing and built-in functions, no arbitrary code
When a Custom Workflow Wins Over Both
Neither Make nor n8n is the right answer for every workflow. Some use cases need a custom build — and being honest about that is how vendor-neutral firms like Layer3 Labs save clients real money.
Custom typically wins when the workflow needs to live inside your existing application, when it has unusual data shapes that a node graph would mangle, or when it has compliance requirements neither tool can satisfy out of the box (granular audit logging, specific data residency, custom encryption).
A common pattern we see: a client starts on Make for a quick proof of concept, hits the per-operation ceiling, moves to self-hosted n8n, then ports the most critical 1–2 workflows to a custom-coded service for performance and auditability — and keeps the rest on n8n.
The decision criterion is information gain per dollar. If a no-code platform gives you 90% of the workflow at 10% of the cost of custom code, use the platform. If you are hitting limits at 70% complete, code it.
How to Choose Between Make and n8n
Use Make if you are a non-technical operator, your workflows are short (under 10 steps), your volume is under 10,000 operations per month, and you have no self-hosting requirement. Make Core at $9–$10.59/month will likely cover you for a year.
Use n8n Cloud if you want the same managed experience but expect to run multi-step workflows where step count would burn Make credits. The flat per-execution price is more predictable for ETL, scraping, and multi-step AI flows.
Use n8n self-hosted if you have engineering capacity (or a partner like Layer3 Labs), need data residency, or expect to scale above 80,000 operations per month. The economics tilt sharply at volume.
Use a custom build if the workflow is mission-critical, lives inside your product, has unusual data shapes, or has compliance requirements neither tool can satisfy. Most SMBs need this for at most 1–2 workflows in their stack.
- Make: easiest learning curve, best for non-technical operators
- n8n Cloud: predictable per-execution pricing for multi-step flows
- n8n self-hosted: lowest unit cost at volume plus data sovereignty
- Custom build: when the workflow is part of your product or compliance demands it
The Verdict
For most small and mid-sized businesses in 2026, Make is the right starting point and n8n is the right scaling destination. Start on Make if your workflows are short and your team is non-technical. Move to n8n when step counts, volume, or data residency tip the math.
Pick Make when you need the fastest visual builder, the broadest pre-built integration catalog, and no infrastructure to manage. Pick n8n when you need self-hosting, per-execution economics, or code-level flexibility inside your workflows.
If you are unsure which tool fits, the right starting move is a workflow audit — your actual processes, volumes, and compliance constraints decide this, not a comparison table.
Researched from primary vendor documentation and public regulator sources. Pricing and availability are accurate as of Jun 25, 2026 and can change — confirm current terms with each vendor before you buy.
Frequently Asked Questions
- Make is generally better for small businesses without engineering staff because of its gentler learning curve, larger pre-built integration catalog (~2,000+ apps), and lower starting price (~$9/month). n8n is better for small businesses with technical capacity, higher volumes, or data residency needs because it can be self-hosted on a $20 VPS and bills per workflow execution instead of per step. Most SMBs we work with at Layer3 Labs start on Make and migrate specific high-volume workflows to n8n once they hit operation ceilings.
- n8n is cheaper at scale, especially above 80,000–100,000 operations per month. Make charges per operation (one credit per module step), so a 20-step workflow run 5,000 times consumes 100,000 operations. n8n charges per execution — that same workflow consumes 5,000 executions. Self-hosted n8n on a $20/month VPS handles unlimited executions; Make Core plus operation packs at the same volume runs roughly $109/month. For low-step, high-frequency flows under 10,000 ops/month, Make is often cheaper because the $9 plan covers it.
- Yes for most workflows, plus more — but Make has a larger pre-built integration catalog and a friendlier visual builder. n8n covers roughly 500+ native integrations plus a universal HTTP node that connects to any REST API, while Make covers ~2,000+ apps with often deeper trigger and action support per app. n8n adds capabilities Make does not have: self-hosting, full JavaScript and Python in a Code node, and native LangChain AI agent nodes. Where Make often wins is time-to-first-workflow for non-technical users wiring popular SaaS tools together.
- No, Make cannot be self-hosted. Make is a closed-source, cloud-only SaaS platform with EU or US region selection on its own infrastructure. n8n is open source under the Sustainable Use License and can be self-hosted via Docker, Kubernetes, or directly on a VPS, keeping all workflow data, API keys, and logs inside your own infrastructure. This is the deciding factor for many regulated businesses in legal, healthcare, and financial services.
- Make has the easier AI on-ramp; n8n has the more flexible AI workflows. Make ships drag-and-drop AI agent modules, OpenAI, Anthropic, and other model nodes inside its visual builder — ideal for a non-technical operator building a single-step AI flow. n8n ships native LangChain nodes, a Code node that runs any Python or JavaScript AI library, and an HTTP node for any model API — better for multi-step AI agents, custom embeddings, retrieval flows, or branching reasoning. Token costs in either tool pass through to the model provider; the orchestrator is just the orchestrator.
- Choose a custom build when the workflow must live inside your existing application, when it has unusual data shapes a node graph would mangle, or when it has compliance requirements neither tool can satisfy (granular audit logs, specific encryption, custom data residency). For most SMBs, this applies to at most 1–2 workflows in the stack — the rest run fine on Make or n8n. A practical pattern: start on Make, migrate to self-hosted n8n at volume, code the 1–2 most critical workflows custom for performance and auditability.
Not Sure Whether Make, n8n, or a Custom Build Fits Your Business?
Layer3 Labs is vendor-neutral. We will audit your current workflows, map them against Make, n8n, and custom-build options, and give you a clear recommendation based on your data volume, compliance needs, and team capacity — not on what we resell.
Book your free workflow audit