Make vs n8n (2026): A Five-Criteria Scorecard

One question settles most of this comparison before any feature does: are you willing to run a server? Say yes and n8n opens up — self-hosted, real code at every step, one flat execution per workflow run. Say no and Make is the shorter path — a managed cloud you never patch, with a visual canvas built for people who don't. Both give you connected nodes, a wide service catalog, and branching, looping, and error recovery, so a form-to-spreadsheet-to-Slack job with an AI step on the end runs fine on either.

Five criteria draw the line: who runs the servers, how the bill is calculated, how far the code and AI ceiling goes, how much connects out of the box, and what you carry operationally. Each one below goes to whichever tool earns it.

Control: who runs the servers

This criterion is binary, not a sliding scale. Make is a fully managed SaaS, so there's nothing to host, patch, scale, back up, or secure. Even the free tier lives entirely in Make's cloud, and it offers EU data residency without you standing up a box. The one thing it can't do is put the software on your own hardware: Make is cloud-only, with no self-host path.

n8n makes the opposite bet. It runs on your infrastructure, in Docker, behind your firewall, with a free source-available Community edition under its Sustainable Use License, plus a self-hosted option on the Business and Enterprise cloud tiers. That free edition hands you the DevOps in exchange: servers, uptime, updates, and backups all become your job. If your requirement is GDPR, on-prem, or full control over where the data sits, n8n is the only one of the two that can meet it. If you'd rather never own that work, Make takes it off the table completely.

Edge: n8n when you need the control, Make when you want the job gone.

The bill: credits versus executions

The two platforms don't just charge different amounts, they charge in different units, and that unit tends to matter more than the sticker on the entry plan. Make bills in credits. n8n bills in full executions.

Make's pricing rides a credit slider, quoted here at the 10,000-credit tier. The free plan gives you 1,000 credits a month, 2 active scenarios, a 15-minute minimum interval, and 7-day logs, with the full app catalog open. The first paid tier worth counting is Core, around $9-12 a month depending on billing cadence — roughly $9-10.59 billed annually, closer to $12 month to month. Core unlocks unlimited active scenarios, a 1-minute minimum interval, the Make API, and 30-day logs. Pro sits around $16-21 a month and adds priority execution, full-text log search, and custom variables. Teams runs about $29-38 a month for multi-user access, roles, and shared templates. Enterprise is a custom quote, home to SSO, audit logs, 24/7 support, an SLA, and overage protection. One credit equals one standard module action; AI modules and code cost more, with Make Code metered at roughly 2 credits per second. Annual billing shaves 15% or more. Run past your quota and Make keeps your scenarios going anyway, quietly purchasing extra credits on your behalf, tacking a 25% surcharge onto them, and passing the total to your invoice.

n8n prices in euros and treats one full workflow run as a single execution, however many steps it holds. The self-hosted Community edition is free and source-available with no execution cap, provided you run it yourself. On managed cloud, Starter is 20 EUR a month billed annually for 2,500 executions, 5 concurrent runs, and unlimited users and workflows. Pro is 50 EUR a month annually for 10,000 executions and 20 concurrent runs. Business is 667 EUR a month annually for 40,000 executions and adds a self-hosted option. Enterprise is a custom quote with 200+ concurrent runs, hosted or self-hosted. Annual billing saves about 17% against monthly. Starter and Pro come with a no-card trial; the Business trial asks for one.

Why the unit outweighs the sticker: Make charges per module, so every action, every filter (even one that stops the flow), every poll, and every loop iteration consumes a credit. A 1-minute polling trigger fires about 43,200 times a month before it does any real work. Send 12 line items through a 4-module loop and you've spent 48 credits, not 4. n8n logs that same run as one execution no matter the step count, and self-hosted Community runs unlimited executions for free. On simple, low-volume automation the sticker prices land close enough to call it even. On complex, multi-step, or high-volume flows, per-execution billing is dramatically cheaper, and that's the structural reason n8n takes the cost argument at scale.

Edge: roughly even at low volume, n8n as soon as flows get complex or busy.

The learning curve and the code ceiling

For anyone who doesn't write code, Make is clearly the friendlier entry. Its visual scenario builder puts routers, iterators, aggregators, and filters on one drag-and-drop canvas, so a first working scenario is a same-day job rather than a project. A marketer, an ops lead, or a solo builder can ship something today.

n8n is technical by design and rewards a programming mindset, which is exactly why its curve is steeper and it's less welcoming to non-technical users. That steepness isn't really a defect; it's the entry fee for the headroom that follows. n8n carries a built-in JavaScript editor plus Python, available at any step on every plan, alongside custom nodes. Make's code support is narrower and metered: custom apps published to its marketplace go through a review process, and custom functions are gated to higher tiers. When your automation needs real logic at an arbitrary point, n8n has the taller ceiling.

AI agents track the same split. Across 2025-2026, n8n has pulled ahead with a mature AI Agent node, LangChain integration, tool-routing and memory nodes, and native local-model support via Ollama, with full visibility into how the agent reaches a decision. Per-execution billing compounds it: a multi-step, multi-LLM agent run counts as one execution rather than tallying credits at every step. Make ships AI Agents too, launched in 2025 and rebuilt since, but users describe the per-step credit consumption as a black box. For agent workflows and private LLMs, n8n is the more capable pick.

Edge: Make to get a non-coder started, n8n once real code or AI agents enter the picture.

Connector breadth: what works on day one

Turnkey breadth is where Make answers back. It advertises a far larger native-app catalog, roughly 3,000 apps against n8n's ~400 native integrations plus around 1,000 community nodes, so more mainstream SaaS works before you ever need a custom node. Make also markets itself as trusted by 400,000+ organizations.

Edge: Make, comfortably.

Support and the operational load

The last criterion is who catches problems in production. On Make, the managed cloud absorbs error handling, retries, logging, and uptime for you, and the higher you climb the plan ladder the more backing you get, up to 24/7 support and an SLA at Enterprise. On n8n's Community edition, you are the support desk: the servers, updates, and recovery are yours to run, while the paid cloud tiers layer on concurrency and, at Business, that self-hosted option. One thing worth knowing before you commit: n8n's Starter and Pro plans let you trial without a card, whereas the Business trial asks for one.

Edge: Make if you want a vendor on call, n8n if you're comfortable being your own.

Two profiles, two picks

Line the scorecard up against your own project and one of two profiles usually fits.

Choose n8n if you're a developer or a technical team and someone will run a server. You get code-level control, data that never leaves your infrastructure, and the cheaper, more predictable bill on complex, multi-step, and AI-agent work, where per-execution pricing and a free self-hosted edition beat a credit model that auto-charges overages. It's also the only one of the two that satisfies GDPR, on-prem, or compliance requirements, and its built-in JavaScript and Python make it the natural home for real custom logic and private LLMs.

Choose Make if you'd rather ship an automation today than manage anything. A non-developer, an agency, or an ops and marketing team gets a polished visual canvas, the broadest catalog of turnkey connectors, and a fully managed cloud that handles retries, logging, and uptime. Budget-conscious solo builders on simple, lower-volume flows fit here too: the free tier is enough to start and Core stays cheap, and our Make guide gets a first scenario running. Size the plan against your real volume, though, since credits tally on filters, polls, and every loop pass. Still weighing the managed-cloud field itself? Make vs Zapier walks that fork.

FAQ

Does either platform let me host it myself?

Only n8n. It ships a free, source-available Community edition you run on your own infrastructure under its Sustainable Use License, and it adds a self-hosted option on the Business and Enterprise cloud tiers. Make has no self-host path at all — it's cloud-only — though its managed service does offer EU data residency. When on-prem or full data control is non-negotiable, n8n is the answer.

Which one costs less to run day to day?

Volume and complexity decide it. For simple, low-volume automation the entry prices sit close together — Make Core runs about $9-12/mo at 10,000 credits, and n8n Starter is 20 EUR/mo billed annually. Once flows get complex or high-volume, n8n is usually cheaper: it counts one execution per full workflow run, while Make charges a credit for every module, filter, poll, and loop iteration. And if you're willing to run the infrastructure, n8n's self-hosted Community edition is free with no execution cap.

Which is friendlier if nobody on the team codes?

Make. Its visual-first scenario builder is the more polished, beginner-friendly one, and it never asks you to think like a programmer or stand up a server. n8n aims at technical users and has a steeper curve, because its power comes from dropping into real code. So for simple, linear, no-code automations Make is the gentler on-ramp; for code-heavy or AI-agent builds, n8n's flexibility is what pays off.

Which handles AI agent builds better?

n8n, as things stand across 2025-2026. It brings a mature AI Agent node, LangChain integration, tool-routing and memory nodes, and native local-model support through Ollama. Its per-execution billing helps too — a multi-step, multi-LLM agent run lands as a single execution instead of consuming credits at every step. Make does offer AI Agents, launched in 2025 and rebuilt since, but users describe the per-step credit cost as a black box.