n8n vs Make: Which Fits Your Team's Automation Workload?

Choosing between n8n and Make is less about which tool looks nicer and more about how your automation workload is shaped. The two products bill you differently, treat code differently, and have very different stories when AI enters the picture. This post unpacks both tools honestly so you can pick the right one — and shows you why the self-hosting path is more accessible than you think.

How Each Tool Bills You

This is the most important factor at scale, and most comparisons gloss over it.

Make sells operations. Every action a scenario takes — reading a row, sending an email, calling an API, evaluating a filter — costs operations. Paid plans start around $9/mo for 10,000 ops and scale up steeply. A moderately busy workflow that processes 500 records and does three things to each one burns through 1,500 operations per run. Run it twice a day and you're at 90,000 ops/month. That's Core plan territory ($16/mo) — before adding any AI steps.

n8n has a different model entirely. The hosted cloud version bills by executions, but n8n is also open-source and self-hostable. When you self-host n8n, there is no per-execution or per-operation meter — your workflows run as many times as your server allows. That changes the economics dramatically for high-volume workloads.

	Make	n8n (self-hosted)
Billing unit	Operations	Server resources
100k operations/mo	~$16–$29/mo	Flat server cost
Code steps	Limited (JS in HTTP modules)	Full JavaScript / Python in Code node
AI/LLM nodes	Bring your own API key	Bring your own API key
Scenario/workflow triggers	Polling + webhooks	Polling, webhooks, schedule, event
Data transformation	Moderate	Strong (expressions + Code node)
Community nodes	Growing	Large ecosystem

Where n8n Wins

Complex data transformations. n8n has a Code node where you write raw JavaScript or Python. You can manipulate arrays, parse XML, build nested objects, do regex — anything a developer would do in a script. Make's equivalent requires chaining multiple modules or using a limited "Tools" module. If your workflows reshape data substantially, n8n is significantly faster to build and maintain.

Branching logic at scale. n8n's IF, Switch, Merge, and Loop Over Items nodes give you genuine programming control flow. Building a multi-branch CRM sync or a conditional notification router is natural in n8n. In Make, deep branching gets visually crowded and harder to debug.

Webhooks as first-class citizens. Every n8n Webhook node produces a stable HTTPS URL immediately. You paste it into Stripe, GitHub, a CMS, or a form builder and it just works. There is no separate module cost for receiving webhook data.

Self-hosted freedom. You own the code, you own the data, you own the execution. You can inspect every credential, add custom nodes from npm, or modify how the instance behaves.

Where Make Wins

Onboarding speed for non-technical users. Make's scenario builder is genuinely approachable. Drag a module, pick an app from a list, authenticate, map fields — even a marketer with no coding background can build a working scenario in 20 minutes. n8n has improved its UI considerably, but Make still has a shallower initial learning curve.

Native app integrations. Make maintains a large library of pre-built app modules (1,000+), many with step-by-step field mapping guides. For common SaaS connections (HubSpot, Mailchimp, Airtable, Notion), you'll often find a module that just works without any custom HTTP requests.

Iterating on simple linear flows. If your automation is genuinely simple — trigger, look up a record, send a message — Make's visual flow is fast and readable. The operations model only becomes punishing once you're running frequently or processing bulk data.

The AI Cost Reality

Here is where the comparison gets uncomfortable for both tools.

Make has AI modules that connect to OpenAI, Anthropic, and others. Every call to those modules costs: (a) operations on Make's meter, plus (b) API costs on your own account. At volume, that compounds fast. You need a Make plan that covers the operation count and a separate paid API subscription.

n8n has excellent AI and LLM nodes — an AI Agent node, an LLM Chain node, a Vector Store tool set, OpenAI/Anthropic/Gemini integrations. But on both n8n Cloud and self-hosted n8n, you still bring your own API key. The AI execution cost is entirely separate from whatever you pay for n8n itself.

This is the standard across every hosted automation platform: Make, n8n Cloud, Zapier, and most self-hosting providers all expect you to supply and pay for your own AI API keys.

Your Own n8n Instance, AI Credits Already Included

AgentRoost does something none of those platforms do: when you spin up your own n8n instance, AI/LLM credits are already included in the subscription price.

Your AI Agent nodes, LLM Chain nodes, and any other AI-powered steps in your workflows have credits to spend from day one — no OpenAI account, no Anthropic billing dashboard, no API key to paste anywhere. 350+ models available, switchable anytime from the AgentRoost workspace manager.

The pricing is $19.99/mo all-in. That bundles server capacity, AI/LLM credits, SSL, the public subdomain (https://<your-id>.agentroost.app), automatic updates, and zero DevOps on your part. Cancel anytime. 14-day money-back guarantee.

How to Get Your Own n8n Instance on AgentRoost

1. Sign up at agentroost.app — email/password, or one click with Google, Microsoft, or Discord.
2. Pick the n8n framework from your dashboard.
3. Name your instance (this becomes your subdomain).
4. Your private n8n editor opens at https://<your-id>.agentroost.app. Log in with your own credentials — this instance is yours.
5. Build your first workflow. Drop an AI Agent node. It already has credits behind it. No API key prompt, no "connect your OpenAI account" modal.

Webhooks you create inside n8n get a stable public HTTPS URL automatically — no tunnel, no Cloudflare, no ngrok.

If you're coming from Make and have existing scenarios, n8n's importer can handle many Make scenario JSON exports, or you can rebuild them using n8n's equivalent nodes (Make's "Router" → n8n's Switch, Make's "Iterator" → n8n's Loop Over Items).

Who Should Pick What

Pick Make if: your team is non-technical, your automations are simple and linear, you need a specific niche SaaS module that n8n doesn't have, and your monthly operation count stays comfortably within your plan. It is a genuinely good product for these cases.

Pick n8n (your own instance) if: you process meaningful data volumes, need custom code steps, want AI nodes that actually work without a separate API account, or care about owning your workflow data. The self-hosted model removes the per-execution meter and the AgentRoost path removes the DevOps overhead entirely.

The honest cost comparison at moderate scale: a team running 500k operations/month on Make would be on a $59/mo plan, plus separate AI API costs. The same workload on your own n8n instance at AgentRoost sits at $19.99/mo with AI credits included — and no execution ceiling.

Compare plans · See what your own n8n instance looks like