Zapier vs Make: The Cost-Per-Execution Math Most Guides Skip

The wrong question and the right one

Most "Zapier vs Make" guides answer "which has the cleaner interface" or "which is cheaper at the entry plan." Both are the wrong question.

The right question: which billing model fits the shape of the workflows you actually run? Zapier bills per successful action step. Make bills per module execution. Those two models look similar at 100 runs per month. They diverge by 4—15x at 50,000 runs per month for the same logic. Picking the wrong one is the most common reason automation budgets blow up in month four.

Both tools play a role in how we build our AI automation service depending on the complexity and volume involved.

This post is a buying framework, not a feature dump. Three sections: how each platform actually bills, the five workflow shapes that decide your answer, and the 10-minute projection to run before signing up. If you want a coordinated system that picks the right tool and wires the automation into pipeline reporting, our AI automation service is where that ends up.

How each platform actually bills

Read each company's pricing page before you read a comparison post. Both have changed materially in the last twelve months and most third-party guides cite stale numbers.

Zapier bills per task. A task is a successful action step inside a Zap. Triggers are free. Filters that stop a Zap before any action runs are free. Multi-step Zaps that finish all the way through count one task per action. So a Zap that triggers on a Stripe payment, looks up the customer in Airtable, posts to Slack, and writes a row to Google Sheets consumes three tasks per run.

Plans (annual billing, per Zapier's pricing page): Free (100 tasks, two-step Zaps only), Professional from $19.99/month for 750 tasks, Team from $69/month for 2,000 tasks, Enterprise custom. Task ceilings scale up to 2 million tasks at roughly $5,999/month on the top tier. Annual prepay saves about a third versus monthly.

In 2026 Zapier also introduced a separate Activity Credit meter for its Agents product. Agents are autonomous and decide their own next action, so Zapier unbundled them from the task counter — every tool call, web search, or knowledge query an Agent makes counts as one activity. Free plans include 400 activities; the Pro Agent add-on adds 1,500 for $33.33/month annual. If you are running Zapier Agents, your old task projection no longer covers the bill.

Make bills per operation, which it has rebranded to credits as of August 2025. One module execution equals one credit for standard automations. Triggers count. Filter checks count. Router branches count. Iterators count once per loop pass. A scenario with eight modules that runs 1,000 times consumes 8,000 operations.

Plans (per Make's pricing page): Free (1,000 credits, 2 active scenarios, 15-minute minimum interval), Core from $10.59/month for 10,000 credits, Pro from $18.82/month for 10,000 credits plus priority execution and full-text log search, Teams from $34.12/month with team roles, Enterprise custom. The November 6, 2025 pricing adjustment changed extra-credit costs and tweaked Core and Pro credit limits — older comparison posts citing Make's pre-2025 numbers undercount real costs by 20—40% depending on plan.

The structural difference is everything that follows. Zapier's bill scales with how much work finishes. Make's bill scales with how much work is attempted, including every check, route, and poll that returns nothing.

The five workflow shapes that decide your answer

The platforms are roughly equivalent at simple, low-volume work. Once you push past 5,000—10,000 monthly runs or add branching, the model you picked starts to matter.

Shape 1: Simple linear, low volume. A two-step Zap or three-module scenario, firing under 1,000 times a month. Pick whichever you find easier to build. The cost gap is under $20/month either way.

Shape 2: High-frequency polling. A workflow that watches an inbox, an Airtable view, or a Notion database for new records. Zapier's polling triggers do not consume tasks until an action actually runs. Make's polling triggers consume an operation every poll, whether or not new data showed up. At a 5-minute polling interval that is 288 operations per day, or 8,640 per month, before any real work happens. If you run six polling scenarios you are inside one Core plan's entire 10,000-credit budget on triggers alone. Webhook triggers eliminate this leak on Make. Every minute you can convert polling to webhooks saves real money.

Shape 3: Branching with rejected paths. A Zap with two filter steps that reject 80% of records before any action runs costs almost nothing in Zapier. In Make the same logic still spends one credit per filter check, every run, on every record. At 10,000 monthly runs that is 20,000 operations spent on filters you do not see in the final output. Make's branching is more powerful; Zapier is meaningfully cheaper on workflows where most records get filtered out.

Shape 4: Iterators and aggregators. A scenario that processes 50 line items per order via an iterator counts 50 operations per loop pass. At 1,000 orders per month that is 50,000 operations for a single scenario. Zapier's Looping app handles the same logic differently; each loop iteration runs a sub-Zap whose actions count as tasks. The cost depends on how many actions sit inside the loop. Make is usually still cheaper here, but the gap is smaller than the "Make wins on volume" headline suggests.

Shape 5: Multi-module branching at high volume. A scenario with 10 modules that runs 20,000 times per month consumes 200,000 operations. That is well above the standard Core/Pro/Teams 10,000-credit base and requires either a higher operation tier or extra credit purchases (~$9 per additional 10,000). The same workflow in Zapier with 6 action steps (triggers and filters free) consumes 120,000 tasks — comfortably inside the Team plan's higher tiers but at materially higher list price. At this scale Make is consistently 4—15x cheaper than Zapier for equivalent logic, which lines up with what third-party benchmarks like Make's own comparison and independent reviews report. The reason it gets reported as "Make is just cheaper" is that most teams are running shapes 2 and 5.

The 10-minute projection

Before you sign up, run this. The exercise is more useful than any feature comparison.

1. List your top five workflows. Not "everything you might automate" — the five that actually run more than 100 times a month each.
2. For each workflow, count two numbers. The number of action steps that succeed per run (this is your Zapier task count per run) and the total number of modules including triggers, filters, and routers (this is your Make operation count per run).
3. Multiply by projected monthly runs. A workflow firing 5,000 times a month with 3 successful actions burns 15,000 Zapier tasks. The same workflow with 8 modules in Make burns 40,000 operations.
4. Sum across all five workflows. That number is your monthly volume on each platform.
5. Pick the plan tier on each platform that covers that volume. That is your real monthly cost. Multiply by 12 to see the annual delta. For most B2B teams running 20K—100K monthly workflow executions the gap is between $600 and $4,800 per year. That is enough money to pay attention to.

If projection is more than $200/month on either side and you are about to commit annually, build the same five workflows in both free tiers first. Both platforms let you wire most of a real scenario without paying. The friction of doing this once is much smaller than the friction of being locked into the wrong platform for a year.

Where each platform actually loses

Honest weaknesses, because the comparison posts that claim either platform "just wins" are wrong.

Zapier loses on cost at scale and on workflow complexity. Multi-branch, multi-iterator scenarios are awkward in Zapier's step-by-step UI and burn through tasks faster than the same logic in Make. If your workflows look like flowcharts, not lists, the visual canvas in Make is built for that and the operation pricing usually wins.

Make loses on polling cost, on debugging at lower tiers, and on agency-grade reliability for time-sensitive triggers. Polling-heavy workflows leak operations whether or not work happens. Pro is the first plan that gives full-text execution log search and priority execution. Without it, diagnosing why a scenario silently failed inside a router branch is genuinely painful. Make's app catalog, while comparable to Zapier's in count, also has more long-tail integrations maintained by community rather than the vendor, which means more drift, deprecations, and silent failures over a 12-month engagement.

Both lose against custom code at very high volume. Above roughly 200,000 monthly workflow runs, the math starts favoring either self-hosted n8n or a small custom service over either commercial platform. That is a separate buying decision. It does not argue against starting with Zapier or Make.

The platform is the substrate, not the system

Most teams treat "we picked Zapier" or "we picked Make" as the answer. The platform is the substrate; the workflows on top of it are what produce pipeline.

The workflows that actually move revenue at B2B service firms live in the unglamorous middle layer: lead-source attribution into CRM, follow-up sequence triggers based on signal data, waterfall enrichment that fills missing fields before a rep sees the record, CRM automation that routes inbound to the right owner inside two minutes, weekly reporting that rolls up booked-call counts by source.

Each of those touches three to five systems, fires a few thousand times a month, and breaks quietly when it breaks. Your automation platform, whichever you pick, needs to handle that load without you noticing the bill until renewal. The way you find out it is not handling it is by watching the monthly cost climb past projection while pipeline stays flat. By then you have already paid for a year of the wrong choice.

If you would rather have someone else do the projection, build the workflows, and report pipeline impact monthly, that is what our AI Marketing Department is for. We pick the platform that fits your shape, build the automations against booked-call outcomes, and own the cost-per-execution math so you do not have to. The AI automation playbook walks through the same logic on your own time if you want to start there.

The takeaway is small but worth saying once more: Zapier and Make are both good. Picking the wrong one for your workflow shape costs four to fifteen times more than the right one. Run the projection before you sign anything.