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

Zapier is named more often, but only just. It appears in 50 of 50 recorded AI answers and Make in 49 of 50. The real gap is order. Zapier is named first in 35 of 50 answers and Make in 8 of 50. Both counts come from ten AI models answering five fixed buyer questions in the 2026-09 edition. They show which product the models name, not which one is better.

TL;DR

• Treat presence as a tie. Both products make almost every answer, so any shortlist the models give you will hold both.
• Expect Zapier to be the name the answers open with. Its average position is 1.32 against Make’s 2.08.
• Read the split by buyer, not by model family. Answers that pick Zapier tie it to speed and non-technical teams. Answers that pick Make tie it to branching logic and cost at volume.
• Price the unit before the plan. Zapier bills per task and Make per operation or credit, so the same workflow uses a different number of billable units on each.
• If the choice is really Make against n8n, the counts are just as close: n8n is named in 50 of 50 answers and first in 7.

How often do AI models recommend Zapier and Make?

Both are named in nearly every answer. The difference is how often each one leads. Share is the proportion of the 50 answers that named the product. Named first means it appeared before any other tracked product in that answer.

Zapier is also the category leader, so it doubles as the reference row. n8n is shown because it sits between the two in the automation platform index.

The named gap is a single answer. The order gap is large. Make’s named share runs 82 points ahead of its named-first share. Zapier’s runs 30 points ahead. In plain terms, the models treat Make as a standard second or third name and Zapier as the name they start with.

Which models prefer Zapier, and which prefer Make?

On naming alone, the models barely separate them. Every model names Zapier in 5 of 5 answers. Nine of the ten also name Make in 5 of 5.

The one miss belongs to Perplexity (Sonar Pro), whose figure is Make (80% of its 5 answers). It also pulls the Perplexity family to Make (90% of that family’s 10 answers). The OpenAI, Anthropic and Google families name Make in every answer.

The lean shows up in what each model recommends, not in whether it names the product.

GPT-5.6 Sol leans Zapier. Its first, 2026 and comparison answers all lead with Zapier. Its operator answer pairs Zapier with n8n and leaves Make out of the headline advice. Its AI-workflows answer picks n8n.

GPT-5.6 Luna leans Make. Its first, 2026 and operator answers each make Make the default. Its comparison answer gives Zapier the default for nontechnical teams and gives Make the visual-power-and-value slot. Its AI-workflows answer picks n8n. This is the sharpest disagreement in the panel: two OpenAI models, opposite defaults.

ChatGPT (GPT-5.6 Terra) splits. Its first answer calls Make best overall for a startup operator. Its 2026 and AI-workflows answers lead with Zapier. Its operator answer picks n8n Cloud.

Claude (Claude Sonnet 5) leans Zapier, with Make as the alternative. It ranks Zapier first for non-technical operators. In its 2026 answer it offers Make as the choice for more power at lower cost.

Claude Opus 5 sequences them. Zapier first, Make once workflows get complex. Its full line is quoted below.

Claude Fable 5 leans Make. Its first answer splits the field by need. Its 2026 answer says to start with Make unless the team is technical.

Gemini (Gemini 3.6 Flash) splits. Its first and comparison answers put Zapier at the top. Its 2026 and operator answers put Make at the top. Its AI-workflows answer leads with n8n.

Gemini 3.5 Flash names both in all five answers and opens its AI-workflows answer with n8n rather than either product.

Perplexity (Sonar Pro) splits. It makes Make the default in its 2026 and operator answers. It gives Zapier the lead in its first, comparison and AI-workflows answers.

Sonar Reasoning Pro leans Make for the default and Zapier for speed. It names Make the all-round pick in its first answer and recommends starting with Make in its 2026 answer. Its comparison and AI-workflows answers lead with Zapier.

The pattern across the panel: when a question asks what a startup operator should adopt, Make gets the recommendation more often than its named-first count suggests. When the question asks for a comparison of the field or a tool for AI workflows, Zapier or n8n takes the lead.

What do the answers say about each?

The recorded answers rarely pick one product outright. Most attach a condition.

“Best overall for a startup operator: Make.” (ChatGPT, GPT-5.6 Terra)

“Zapier remains the safest default” (GPT-5.6 Sol)

“for most startup operators, start with Zapier. Move to Make if your workflows get branchy and your volume climbs.” (Claude Opus 5)

“I’d recommend starting with Make as your primary automation platform” (Sonar Reasoning Pro)

The condition is almost always who builds and maintains the workflows. Zapier is tied to teams without technical help. Make is tied to workflows with branches, loops and volume.

How do Zapier and Make differ?

They charge for different units, and the captured guides aim them at different builders.

Pricing model. Zapier pricing is task-based. A task is typically used when a Zap successfully completes an action step. Zap triggers do not use tasks. Make pricing is based on credits or operations. In Make, an operation is generally a module run. Make usage also rises with the number of bundles or records a scenario processes. Both offer a free tier for basic testing. No plan price is recorded for either product in this edition.

The guides disagree on what that means in practice. OpFlow says Make.com is typically cheaper than Zapier at equivalent volumes. Loudachris says Make.com is typically several times cheaper than Zapier for the same workload at scale. AutomataAI says Make’s equivalent tiers run similarly to Zapier’s mid-tier plans for a small business.

Who Zapier is for. Zapier uses a linear, step-by-step interface that OpFlow describes as easy to learn and suited to simple workflows. Zapier tends to have the wider connector library. AutomataAI calls Zapier’s support and documentation the most mature among the platforms it compares. On data location, Zapier is cloud-only with data processed on US servers.

Who Make is for. Make.com uses a visual canvas with branches, routers, filters and parallel paths. It has a built-in JSON parser plus iterator and aggregator modules for processing lists of data. AutomataAI describes a steeper learning curve than Zapier. On data location, Make.com is cloud-only but offers EU data centre options.

What the models name each for. In the recorded answers, Zapier is attached to speed, app breadth and non-technical teams. Make is attached to visual building, branching logic and value per dollar.

When should you pick Zapier?

Pick Zapier if you want the product the AI answers most often open with, and your workflows are short and linear.

• It is named first in 35 of 50 answers, the highest named-first count among the 14 named products.
• Every one of the ten models names it in all five answers.
• OpFlow recommends it where automations are simple, with no branching logic.
• Peregrine Automations positions it for setups that non-technical staff will maintain.
• A niche vertical tool is a reason on its own, because Zapier tends to have the wider connector library.

The Zapier vendor page holds its full record for this edition.

When should you pick Make?

Pick Make if your workflows branch, reshape data or run often, and you accept that fewer answers lead with it.

• It is named in 49 of 50 answers, so a shortlist built from AI answers will almost always include it.
• Only 8 of 50 answers name it first, so the case for it usually arrives after Zapier’s in the answer.
• Peregrine Automations recommends it where you need multiple paths, complex logic and data reshaping.
• OpFlow points to it for workflows expected to run at moderate to high volume.
• For Australian bookkeeping stacks, Loudachris says Make.com has the strongest native MYOB integration of the platforms it compares.

The Make vendor page holds its full record for this edition.

How this sits against the Zapier vs Make guides

The ranking comparison pages compare features and costs. This page counts what AI answers name. Each ranking page captured for this comparison is published by a business that sells automation work.

OpFlow compares interface, pricing, data handling, integrations and support for Australian small businesses. Its closing section offers a free Automation Assessment.

AutomataAI compares Zapier, Make and n8n, and argues that none of them can handle a request that does not match a pre-built rule. It describes its own work as helping mid-market Australian businesses deploy AI automations.

Peregrine Automations gives a small-business decision table and a set of scenarios, with pricing units linked to each vendor’s help pages. Its closing section offers a done-for-you Automation Audit.

Loudachris recommends Make.com as the default for most Australian small businesses. The author links to his own Make.com automation service from the same page.

None of these pages is published by Zapier or Make. One recorded answer raises a caution about the wider field of comparison content:

“most of the comparison articles ranking these tools are affiliate-monetized or published by the vendors themselves” (Claude Opus 5)

What this page adds is the layer those guides do not measure: which product ten AI models name, in what order, model by model, from a fixed and published set of questions.

How the sample was built

10 models x 5 fixed prompts = 50 recorded answers. One answer was recorded per model and question. 15 vendors were tracked and 14 were named. The method page sets out how answers are collected and counted.

The five questions, verbatim:

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

The ten models, by family:

• OpenAI, 15 answers: GPT-5.6 Sol, ChatGPT (GPT-5.6 Terra), GPT-5.6 Luna.
• Anthropic, 15 answers: Claude Opus 5, Claude (Claude Sonnet 5), Claude Fable 5.
• Google, 10 answers: Gemini (Gemini 3.6 Flash), Gemini 3.5 Flash.
• Perplexity, 10 answers: Perplexity (Sonar Pro), Sonar Reasoning Pro.

What these counts cannot tell you

These counts measure presence in AI answers, and nothing about product quality, uptime, support or fit with a particular stack. Being named is not the same as being recommended, because an answer can name a product only to warn against it. Each model answered each question once, so a single answer can move a per-model count. This is one dated snapshot from the 2026-09 edition. Product names are matched as strings. Answers came through model APIs and can differ from what a consumer chat app shows. The prompts were in English and framed around a startup operator. No position on this page is sold, sponsored or influenced by either vendor.

Frequently asked questions

Should I use Zapier or Make?

It depends on who builds the workflows. The models name both in nearly every answer, and Zapier comes first in 35 of 50. Answers that recommend Zapier tie it to speed and non-technical teams. Answers that recommend Make tie it to branching logic and cost at volume. Peregrine Automations draws a similar line, with Zapier for mostly linear workflows and Make for multiple paths and complex logic.

How much is Make vs Zapier?

The two charge in different units, so compare your own workflow rather than headline plan prices. Zapier counts a task for each successful action step. Make counts an operation or credit for each module run. Peregrine Automations advises modelling events per day multiplied by steps per run before picking a plan. No plan price is recorded for either product in this edition, and the captured guides disagree on whether Make works out lower.

Which is better, n8n or Make?

The panel does not measure which is better. It measures naming, and there the two are close. n8n is named in 50 of 50 answers, first in 7, at an average position of 2.62. Make is named in 49 of 50, first in 8, at 2.08. Loudachris says n8n can be run on an Australian server so data stays in the country. It lists Make.com as cloud-only with EU data centre options.

What is better than Zapier?

No product in this panel is named more often or earlier than Zapier. It is named in 50 of 50 answers and first in 35. n8n matches its named count but comes first in only 7 answers. Make is named in 49 and first in 8. Whether any of them suits your workflows better is outside what these counts measure.

Can I move from Zapier to Make later?

Yes, but plan for a rebuild. AutomataAI says every workflow needs to be rebuilt from scratch in the new platform’s logic. For a business with dozens of active Zaps, it describes that as a multi-week project.