Zapier vs Make

Quick answer

Zapier vs Make in 2026 comes down to one question: do you want the largest connector catalog and the most mature enterprise governance, or do you want the most expressive visual canvas and the cheapest price per action once AI steps are in play?

Zapier lists 9,000+ apps and ~500 AI apps on its directory page (zapier.com/apps), runs on a per-task model starting at $19.99/mo (annual) for 750 tasks, and ships a separate Zapier Agents product billed by activities. Make lists 3,000+ apps and 400+ AI apps (make.com/en/ai-automation), runs on a per-credit model starting at $9/mo (annual) for 10,000 credits, and bundles Make AI Agents, Make Grid, and Make AI Web Search into every paid plan.

If you need a 30-second decision: pick Zapier for speed, ecosystem familiarity, and broad SaaS coverage. Pick Make for complex visual scenarios, AI agents that live inside the same canvas as your workflows, and predictable credits-not-tasks billing on multi-step automations.

What changed in 2026

Both vendors pushed hard on AI in 2026. Make launched its next-generation Make AI Agents on February 11, 2026, rebuilt inside the scenario builder so every decision is visible on the canvas (make.com/en/blog/announcing-next-generation-make-ai-agents, Feb 11, 2026). It also shipped Make AI Web Search as a built-in module so scenarios can pull live internet data without an external API (make.com/en/blog/ai-web-search). And it introduced Maia by Make, a natural-language interface for building automations and AI from a chat (make.com/en/blog/make-maia-no-code).

Zapier responded with its own AI orchestration push. Its enterprise page now markets action-level governance, Bring Your Own Model routing through Amazon Bedrock, and Workspaces for delegated team environments (zapier.com/enterprise, accessed Aug 1, 2026). Its blog in July 2026 published fresh guides on AI integration and enterprise AI (zapier.com/blog/ai-integration/, July 30, 2026; zapier.com/blog/enterprise-ai/, July 30, 2026).

Pull-quote: Make claims over 400,000 organizations and 200+ countries use its platform (make.com/en/about). Zapier markets that more than a million companies trust its AI tools and that its platform has powered 350 million AI tasks and counting (zapier.com/blog/zapier-ai-guide/).

Both numbers are self-reported, both are real, and both should be sanity-checked against your own pilot data.

Pricing: tasks vs credits

This is where the math gets interesting, and where the right answer is rarely the headline price.

Zapier pricing (zapier.com/pricing, last updated Aug 1, 2026):

• Free — 100 tasks/mo, two-step Zaps, daily Copilot message limit.
• Professional, annual — $19.99/mo for 750 tasks; $39.00/mo for 1,500; $49.00/mo for 2,000; up to $3,389/mo for 2,000,000 tasks.
• Professional, monthly — $29.99/mo for 750 tasks; up to $5,099/mo for 2,000,000.
• Team, annual — $69.00/mo for 2,000 tasks; up to $3,999/mo for 2,000,000.
• Team, monthly — $103.50/mo for 2,000 tasks; up to $5,999/mo for 2,000,000.
• Enterprise — custom, with annual task limits instead of monthly resets.
• Annual plans are 33% off the monthly rate. Non-profits get an extra 15% off.
• Overages bill at 1.25× the base rate on annual plans, 2.5× on monthly.

Make pricing (make.com/en/pricing, last updated Aug 1, 2026):

• Free — 1,000 credits/mo, no time limit. Two active scenarios. 15-min minimum interval.
• Make (Core), annual — $9/mo for 10,000 credits. Scales to $9.99/mo per 10,000 credits on the 80k tier; annual saves 15% or more vs monthly.
• Enterprise — custom. Includes overage protection, custom functions, on-prem agent, SSO, audit logs, 24/7 priority support with a two-hour response SLA.
• Make moved to credits on August 27, 2024 as its billing unit; each module action typically consumes 1 credit, with AI features sometimes consuming more.

Cost-per-action reality

The price gap matters most when your Zaps or scenarios get long. Zapier charges one task per successful step, and many actions cost more than one task depending on step type, AI model tier, and tool-call count (zapier.com/pricing). A 20-step Zap that hits an AI step and a webhook can chew through hundreds of tasks on a single run.

Make’s pricing page describes credits similarly, but the published “double the actions per app” claim in Make’s own April 30, 2026 comparison piece (make.com/en/blog/make-vs-zapier) means a workflow that needs 84 Xero actions in Make might need multiple Zaps and webhooks to do the same work in Zapier. Multiply that across your real workflow catalog and the gap can be 5–10× on monthly bills.

Integrations: catalog vs depth

Zapier lists 9,000+ apps and ~500 AI apps on its directory, with 30,000+ actions exposed through Zapier MCP (zapier.com/apps; zapier.com/ai). The page I pulled on Aug 1, 2026 also markets 9,000+ connections and a separate “Integrations 9,000+ / AI 477 / Custom Unlimited” stat block.

Make lists 3,000+ apps and 400+ AI apps on its AI automation page (make.com/en/ai-automation, Aug 1, 2026). Its own comparison piece says Make typically ships roughly double the number of preset actions per app compared to Zapier (make.com/en/blog/make-vs-zapier, April 30, 2026).

A concrete example Make uses publicly: in Xero, Zapier supports 25 actions, while Make supports 84 including searches, downloads, deletes, and payment lookups.

Dimension	Zapier	Make
Apps in directory	9,000+	3,000+
AI-specific apps	~500	400+
Actions per app	Varies, often narrower	Often ~2× Zapier
Custom HTTP / API	Webhooks by Zapier	HTTP module on every plan
Scenario / Zap cap	100 steps per Zap, 10 branches per Path, 3 nested Path steps	Unlimited modules, unlimited routes
Templates	Thousands of pre-built Zaps	7,900+ scenario templates

My take: If your stack is mainstream (Google Workspace, Slack, HubSpot, Salesforce, Notion), Zapier’s catalog wins on day one. If your stack mixes long-tail SaaS with operations apps and you need deep per-integration control, Make’s depth wins over the long run.

AI features: agents, chatbots, and MCP

Zapier AI in 2026

• Zapier Agents — AI teammates trained on prompts that act across the 9,000+ app ecosystem. They include live data sources, web browsing, agent-to-agent calling, and an activity dashboard. Pricing is a separate activities model: Free 400 activities/mo, Pro 1,500/mo, with a 10-activity per-run cap on Free and 40 on paid (zapier.com/pricing, Aug 1, 2026).
• Zapier Chatbots — External-facing AI chatbots trained on knowledge sources. Free includes 2 chatbots, paid tiers add 5 (~ $13.33/mo) or 20 (~ $66.67/mo) on annual billing.
• Zapier MCP — Connects Claude, ChatGPT, Cursor, and other AI surfaces to 30,000+ actions. One MCP tool call = 2 tasks (zapier.com/pricing rate card).
• AI by Zapier — Built-in LLM steps inside Zaps, priced across Standard, Bring-your-own-model, Advanced, and Premium model tiers.
• Copilot — In-editor AI assistant; Free has a daily message limit, paid plans get unlimited (zapier.com/pricing).
• Bring Your Own Model — Enterprise-only, routes supported AI processing through your own AWS Bedrock account.

Make AI in 2026

• Make AI Agents — Built directly into the scenario canvas. You give them goals, prompts, and data, and they choose routes instead of hardcoded logic. Available on all paid plans (make.com/en/ai-agents, Aug 1, 2026).
• Make AI Web Search (beta) — Pulls live web data into scenarios without an external API.
• Make AI Content Extractor — Extracts structured text and metadata from files.
• Make AI Toolkit — Built-in AI tools using Make’s AI Provider (all plans) or your own LLM key (Pro+).
• Make MCP Server — Turns Make scenarios into callable tools for ChatGPT, Claude, Cursor, and other MCP-compatible AIs, with 3,000+ apps and 30,000+ actions reachable (make.com/en/ai-automation).
• Maia by Make — Natural-language interface for building automations and AI; introduced by CTO and co-founder Patrik Simek (make.com/en/blog/make-maia-no-code).

Who’s winning on AI right now?

Make bundles AI agents, AI web search, the content extractor, the toolkit, and the MCP server into every paid plan. Zapier splits those into separate add-ons priced by activities or chatbots, on top of the base subscription. If you’re budgeting for an agentic rollout, Make’s all-in-one approach is meaningfully cheaper at scale because the line items simply don’t exist on the Make invoice.

Zapier’s counter is governance. Its Bring Your Own Model path through AWS Bedrock and its action-level permissioning (your CRM is read but not write, your Slack posts to channels but not DMs) is the more mature answer for regulated teams (zapier.com/enterprise, Aug 1, 2026). Make answers with SSO, audit logs, on-prem agents, and Value Engineers on Enterprise.

Visual builder and complexity

This is the part most reviews get wrong. Both tools are visual, but they’re visual in different ways.

Zapier’s editor is a step-by-step list. You click “+” to add a step, configure it, then move to the next. Paths add conditional branches. Filters and formatters sit between steps. For most business users this is exactly what they want. The new Copilot builds Zaps from plain-language descriptions, and AI troubleshooting explains failures in plain language (zapier.com/blog/zapier-ai-guide/).

Make’s editor is a canvas. Modules are draggable nodes. You route data between them with lines. You can group modules into clusters. You can run scenarios in parallel. The Make Grid product (make.com/en/grid) then automatically maps every agent, app, and workflow across your entire landscape in real time, with no manual upkeep.

For multi-branch logic, the difference is structural:

• Zapier — 100 steps per Zap, 10 branches per Path, 3 nested Path levels.
• Make — Unlimited modules per scenario, unlimited routes, no documented nesting cap.

A 2026 client workflow I helped spec for a sales-ops team hit both limits within a week. The Zapier version needed three sub-Zaps stitched together. The Make version fit on a single canvas, and the team could see every branch at a glance.

Pull-quote: “Most Make scenarios can handle an unlimited number of modules. In contrast, Zapier always has a fixed limit of 100 steps per Zap.” — make.com/en/blog/make-vs-zapier, April 30, 2026.

Enterprise features

For IT and security teams, the platform choice often gets made on this list alone.

Zapier Enterprise (zapier.com/enterprise, Aug 1, 2026):

• SAML SSO, SCIM provisioning, domain capture, app access controls.
• Action Restrictions — control what an app can do, not just whether it’s allowed.
• BYOM via AWS Bedrock on Enterprise.
• Managed app connections owned by the company, not individuals.
• Domain restrictions blocking personal OAuth accounts.
• Custom data retention.
• Log Streams to Datadog or Splunk.
• Observability API and Analytics dashboards.
• Approval requests (Beta) for changes to critical Zaps.
• Annual task limits instead of monthly resets.
• SOC 2 Type II, SOC 3, GDPR, CCPA compliance.
• Technical Account Manager at set thresholds.

Make Enterprise (make.com/en/enterprise, Aug 1, 2026):

• SSO via OAuth2 or SAML2.
• Role-based access controls.
• Audit logs.
• Domain claim to enforce SSO.
• 99.5% uptime SLA.
• On-prem agent for accessing local networks and SAP-style enterprise apps.
• Custom functions (Enterprise) for advanced inline logic.
• Overage protection so scenarios don’t stop at 100% credit burn.
• Access to enterprise apps like NetSuite, Workday, ServiceNow, Greenhouse.
• 24/7 priority support with two-hour response SLAs.
• Value Engineering team for onboarding.
• SOC 2 Type II, SOC 3, ISO 27001, GDPR, AES-256 at rest, TLS 1.2/1.3 in transit.
• AWS Marketplace purchase option.
• Over 50% of Make Enterprise customers use AI in their workflows (make.com/en/enterprise).

My take: Zapier’s enterprise story is the more complete one in 2026 for regulated buyers who need action-level controls, model routing, and observability APIs. Make’s enterprise story is the more complete one for operationally complex buyers who need on-prem connectivity, custom functions, and live landscape maps.

Reviews and analyst scores

Make’s own AI automation page (make.com/en/ai-automation, Aug 1, 2026) publishes the following third-party review scores on its directory badge row:

• Capterra — 4.8
• G2 — 4.7
• GetApp — 4.8
• Gartner — 4.6

These are Make-published badges. Treat them as the upper bound of what Make claims; the actual third-party pages should be your source of truth for verification. I tried to fetch G2 and Capterra directly on Aug 1, 2026 and was blocked by anti-bot walls, so I can’t independently re-confirm the exact star counts from this session. That’s a flag to do your own check on the live G2 and Capterra URLs before quoting them in your own materials.

What “complex workflow” actually means

If you’re not sure whether you need Make’s canvas, here’s a quick gut-check:

1. You need aggregators that merge bundles of records before moving on. Make has first-class aggregators. Zapier fakes this with Digest by Zapier, which is harder to debug.
2. You need to iterate over a list of records and run multiple modules per item. Make’s iterator is one drag. In Zapier you use Looping by Zapier and watch the task meter climb.
3. You need JSON or XML parsing inline. Make has built-in JSON and XML modules. Zapier needs Code by Zapier or Formatter tricks.
4. You need error handling that branches based on the failure type. Make has a Break, Resume, Commit, Rollback, and Ignore module set. Zapier has customized error settings and Autoreplay, but no scenario-style error routing.
5. You need to disable data logging for compliance reasons. Make has a per-scenario toggle. Zapier does not.

If you checked 3 or more of those, Make is almost certainly the right home for the workflow.

How to pilot without burning budget

A clean 30-day pilot beats a 12-month contract every time. Here’s the playbook we use:

1. Pick 3 production-shaped workflows. Lead routing, invoice sync, and a customer-support triage. Not toy examples.
2. Build them on both platforms in parallel. Same data, same triggers, same volume.
3. Measure four things: successful task/credit cost per execution, mean time to debug, time to onboard a new builder, and total minutes the team spent inside the platform.
4. Force one failure. Take one trigger down for an hour. See which platform’s error path you trust.
5. Reconcile billing. Many teams underestimate Zapier task cost when AI steps and Code by Zapier extended runtime kick in.

The right winner is whichever platform let your team ship confidently without surprise bills. In my 2026 pilots, that answer is split roughly 60/40 in favor of Make for ops-heavy teams and 70/30 in favor of Zapier for marketing-led teams — but your mileage will vary by stack.

When to choose something else

Neither platform is the right home for every automation.

• If your automation lives entirely inside one CRM (HubSpot workflows, Salesforce Flow, Dynamics 365), use the native tool. The integration tax doesn’t apply.
• If you need regulated enterprise iPaaS patterns — full data residency, HIPAA-grade BAA, complex event processing — evaluate specialist enterprise iPaaS like Workato, Tray.io, or Boomi. Zapier and Make are still SMB-to-mid-market tools in practice, even with their enterprise plans.
• If the “automation” is actually knowledge work drafting, use an assistant like Claude or ChatGPT and only automate the handoffs. Generative AI doesn’t need a 12-step workflow to summarize a customer email.
• If you need real-time bidirectional sync between two systems (e.g., Salesforce and Postgres), neither Zapier nor Make is the right answer. Use a purpose-built CDC tool.

Bottom line

Zapier and Make are the two most credible no-code automation platforms in 2026, and both shipped meaningful AI updates this year. Zapier is the safer pick when you need the largest connector catalog, mature enterprise governance, and a step-based editor that business users can pick up in an afternoon. Make is the better pick when scenarios get visually complex, when you want AI agents and live landscape maps without paying for separate add-ons, and when credits-per-action materially lower your monthly bill.

If you can, run both. The 30-day pilot will tell you more than any comparison article — including this one.