n8n vs Make (2026): What ChatGPT, Claude & Gemini Say

The models name both almost every time, and the counts are close to level. n8n was named in 50 of 50 answers and Make in 49 of 50. Make was named first in 8 of 50 answers and n8n in 7 of 50. Make also sits earlier in the average answer, at position 2.08 against 2.62 for n8n. Neither leads the category. That place belongs to Zapier.

This page covers the 2026-09 edition. It counts names in AI answers and makes no judgement on product quality.

TL;DR

• Treat n8n and Make as level on presence. Every model named n8n in every answer, and nine of the ten models named Make in every answer.
• Expect the question to decide the lead pick. Startup-operator answers that opened on one of the two usually opened on Make. Answers to the AI-powered workflows question that opened on one of the two chose n8n.
• Compare the billing unit before the sticker price. Make charges per credit, and n8n charges per completed workflow run.
• Choose by who will own the workflows. Both captured guides place n8n with developers and Make with a wider, less technical audience.

How often do AI models recommend n8n and Make?

n8n and Make sit second and third in the automation-platform category, with almost identical naming counts. n8n was named in all 50 recorded answers. Make was named in 49. Make edges ahead on both ordering measures. It was named first in 8 of 50 answers against 7 for n8n, and it appears earlier in the average answer.

Answer share is the share of recorded answers that named the product. Named first is the share where it appeared before any other tracked product.

The gap that matters sits between being named and being named first. For n8n that gap is 86 points. For Make it is 82 points. The models treat both as fixtures of the answer and rarely as the opening pick. Zapier takes the opening slot in 35 of 50 answers, so a buyer who asks an AI model about automation usually meets Zapier first and then n8n and Make together.

For a buyer already down to these two, the totals give almost no separation. The separation shows up in which questions hand each product the lead. The full category record, with every answer, is on the automation platforms index.

Which models prefer n8n, and which prefer Make?

On naming alone, no model prefers either product. Every model named n8n in 5 of 5 answers. Nine models did the same for Make. Sonar Pro is the one exception: it named Make in 4 of 5 answers, and the answer without Make was its reply to the AI-powered workflows question.

By family, the OpenAI, Anthropic and Google models named both products in every answer. The Perplexity pair is the only family below full coverage for either product, at Make 90%.

The lean shows up in the lead recommendation each answer opens with. Model by model:

• GPT-5.6 Luna opened on Make in every startup-operator question and on n8n in the AI-powered workflows question. It gives the clearest split between the two products in the panel.
• Gemini 3.6 Flash ranked Make first when asked what to recommend in 2026 and what a startup operator should use. It ranked n8n first on AI-powered workflows.
• GPT-5.6 Sol opened on Zapier for the startup-operator questions and paired Zapier with n8n when asked what to use. It named n8n “Best overall” for AI-powered workflows.
• GPT-5.6 Terra split its startup-operator picks between the two. It opened on Make when asked to name specific products and on n8n Cloud when asked what to use.
• Gemini 3.5 Flash placed n8n first in its AI-powered workflows answer.
• Sonar Pro and Sonar Reasoning Pro both made Make their default for a startup operator in 2026. Sonar Pro did the same when asked what to use.
• Claude Fable 5 recommended starting with Make and moving to n8n for technical teams.
• Claude Opus 5 opened on Zapier when asked what to use, placed Make as the next step and kept n8n for engineer-owned setups.
• Claude Sonnet 5 opened on Zapier and offered Zapier or Make as its 2026 pick.

The sharpest disagreement sits inside the OpenAI family. GPT-5.6 Luna made Make its default for startup operators. GPT-5.6 Sol opened on Zapier and reached for n8n as the second platform. Claude Opus 5 and Claude Fable 5 hold n8n back for technical teams. Both Google models send buyers to n8n when AI is the job.

What do the answers say about each?

The recorded answers describe Make as the operator’s default and n8n as the technical team’s choice:

• GPT-5.6 Luna, asked to name specific products: “For most startup operators, I’d choose Make as the default platform.”
• Gemini 3.6 Flash, asked what it would recommend in 2026: “Make strikes the sweet spot between usability and visual complexity.”
• GPT-5.6 Terra, asked what a startup operator should use: “n8n is the best long-term default”
• Sonar Pro, same question: “if you have a developer and want maximum control and lower long-term cost, choose n8n”
• Claude Opus 5, same question: “Move to Make if your workflows get branchy and your volume climbs. Only pick n8n if an engineer will own it.”

The same question drew Make, n8n and a staged path from different models. Their disagreement turns on who will maintain the workflows.

How do n8n and Make differ?

The two charge by different units. Make uses a credit-based pricing model, and most modules in a workflow consume one credit. n8n charges per workflow execution, and a complete run counts once however many steps it holds. n8n also offers a self-hosted Community Edition with no licensing cost. Make runs cloud-first at every subscription level.

Pricing model

On Make, each step in a workflow usually consumes at least one credit. On n8n, the step count leaves the execution count unchanged. The shape of your workflows therefore decides which unit costs less.

Self-hosting moves cost onto your own servers and staff. Make’s comparison page says self-hosting n8n brings infrastructure costs and maintenance overheads. Nick Saraev’s post found Make more cost-effective than n8n’s cloud plan at low usage. The same post warns that Make’s cost climbs as usage scales up. Saraev worked in Make’s older operations unit. Make has since moved its billing to credits.

Make offers a free plan with no time limit. This page records pricing units and leaves plan prices to each vendor’s pricing page.

Who each is for

Saraev writes that n8n markets itself as “for devs, by devs”. He writes that Make markets itself as “for everybody”. Make’s own page says n8n suits developers, data teams and technical businesses. The same page says Make’s visual approach serves users just starting out.

Hosting and code

n8n is open-source, and it also offers a cloud-hosted version. Make, formerly Integromat, is a closed-source service. Everything in Make runs in the cloud and is managed for you.

What the models name each for

The models name Make as the default for a startup operator. They name n8n for AI-powered workflows and engineer-owned stacks. Both readings come from the lead recommendations above.

When should you pick n8n?

Pick n8n if a developer or technical team will own the workflows, or if AI-powered workflows are the main job.

• Every model named it in every answer, 50 of 50 in total.
• On the AI-powered workflows question, each answer that opened on n8n or Make chose n8n.
• A complete workflow run counts as one execution on its pricing, however many steps it holds.
• Its self-hosted Community Edition carries no licensing cost, with servers and upkeep on your side.
• Saraev calls n8n easier for more complex, operationally-intensive applications.

Weigh this count against it: n8n was named first in 7 of 50 answers, against 8 for Make.

When should you pick Make?

Pick Make if the people building workflows are operators without a developer, and you want a managed cloud service with a free tier.

• It was named first in 8 of 50 answers and sits earlier in the average answer, at position 2.08.
• Startup-operator answers that opened on one of the two usually opened on Make.
• Its free plan has no time limit.
• Hosting is fully managed in the cloud, with no servers for your team to run.
• Saraev would start a beginner on Make and move to n8n later as skills grow.

Weigh this count against it: Sonar Pro named Make in 4 of 5 answers, the only gap in either product’s model split.

How this sits against the n8n vs Make guides

The captured Google results for “n8n vs Make” compare features and cost from a builder’s or a seller’s seat. This page counts what ten AI models say when a buyer asks.

Make’s comparison page on make.com is written by Make. It compares the two on pricing, integrations, AI and agentic automation, orchestration, enterprise readiness and support. It closes by calling Make the strongest choice for today’s organisations. Read it as the vendor’s case.

Nick Saraev’s post on nicksaraev.com was published in September 2024 under a 2025 title. He builds the same AI email-categorisation system on both platforms. He then scores builder features one by one, giving Make module availability, connections and webhooks, and giving n8n the rest. He recommends Make for a beginner and n8n as the later step. The post closes by promoting the author’s own automation communities.

n8n publishes its own comparison page on n8n.io, which also ranks for this query.

The guides argue which product is easier or cheaper for a builder. The panel shows what a buyer hears when they ask an AI model, and on that measure the question asked decides which of the two leads.

How the sample was built

10 models x 5 fixed prompts = 50 recorded answers. The five questions, verbatim:

• “What is the best automation platform to connect apps and run workflows for a startup operator? Name specific products.”
• “Which automation platform to connect apps and run workflows would you recommend to a startup operator in 2026?”
• “Compare the top automation platform to connect apps and run workflows options right now.”
• “I’m a startup operator and I need an automation platform to connect apps and run workflows. What should I use and why?”
• “Best automation platform to connect apps and run workflows for AI-powered workflows?”

The ten models come from four families. OpenAI: GPT-5.6 Sol, GPT-5.6 Terra and GPT-5.6 Luna. Anthropic: Claude Opus 5, Claude Sonnet 5 and Claude Fable 5. Google: Gemini 3.6 Flash and Gemini 3.5 Flash. Perplexity: Sonar Pro and Sonar Reasoning Pro. GPT-5.6 Terra fills the panel’s ChatGPT slot and Sonar Pro fills its Perplexity slot. Every model ran with web search. The run was recorded on 2 September 2026. The method page sets out how answers are recorded and counted.

What these counts cannot tell you

The counts measure presence in AI answers. They say nothing about uptime, support, pricing fairness or fit with your stack. Being named also differs from being recommended, because an answer can list a product only to warn against it. Each model answered each question once, so a second run could shift a count. This is one dated snapshot from the 2026-09 edition. Names are matched as strings, including the aliases Make.com and Make (formerly Integromat). The panel records API answers, which can differ from a consumer chat app, and every prompt was in English. The lead-pick reading on this page is an editorial reading of each answer’s opening recommendation and sits outside the counted measures.

Frequently asked questions

Is n8n obsolete now?

The panel shows no sign of it. In the 2026-09 edition every one of the ten models named n8n in all of its answers, and n8n ranks second in the automation-platform category behind Zapier. The panel counts how often AI models name a product. Product health sits outside what it measures.

Is anything better than n8n?

The panel counts who gets named and leaves quality unranked. On that measure Zapier was named first in 35 of 50 answers, against 7 for n8n and 8 for Make. The category record lists every product the models named.

Is make or n8n cheaper?

It depends on the shape of your workflows. Make bills in credits, and most workflow steps consume one. n8n bills per complete workflow run. Saraev found Make cheaper than n8n’s cloud plan at low usage, with Make’s cost climbing as usage grows. Self-hosted n8n carries no licence fee, and it adds server and maintenance costs.

Is make.com the same as n8n?

No. Make, formerly Integromat, is a closed-source cloud service. n8n is open-source and can be self-hosted or run on its cloud offering. The models name the two side by side in nearly every answer.

Can a vendor pay to change these counts?

No. Vendors cannot pay to appear, to be reordered or to be removed. The counts come from the recorded answers alone.