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Airtop Agent Builder Pricing: Plans, Credits and Limits Explained

A practical breakdown of Airtop Agent Builder plans, deployed-agent limits, concurrent sessions, credits and the cost controls that matter before you scale.

Published 2026-09-04 · Updated 2026-09-04 · By Project Monet Editorial Team

Airtop Agent Builder pricing plans, credits, deployed agents and session limits

01

Current Airtop Agent Builder plans

Airtop currently lists Free at $0/month, Starter at $29/month, Professional at $189/month, Enterprise at $558/month and a Custom tier. Airtop also advertises a 10% discount for annual billing with credits provided upfront.

02

Free and Starter: testing and small deployments

The Free plan currently shows 1,000 credits, three simultaneous sessions and one deployed agent. Airtop also lists a one-time 10,000-credit bonus and a seven-day Mark trial or until trial credits are consumed.

Starter is $29/month and currently lists three simultaneous sessions, up to 10 deployed agents, an integrated proxy and support. Its main advantage over Free is deployment capacity rather than higher browser concurrency.

03

Professional and Enterprise: higher concurrency

Professional is currently $189/month with up to 30 deployed agents and 30 simultaneous sessions, plus a custom proxy, Mark and dedicated support. It is the first public tier that materially expands concurrency for teams running several browser workflows in parallel.

Enterprise is currently $558/month and lists unlimited deployed agents with up to 100 simultaneous sessions, alongside a SOC 2 Type II report, Mark and dedicated support. Unlimited deployed agents does not mean unlimited credits, compute or simultaneous browser capacity.

04

How Airtop credits and AI costs work

Airtop says it uses a credit system because its AI APIs can use multiple models and pricing tiers. Each AI API call returns a meta.usage object with the number of credits consumed by that call.

Airtop's documentation says it does not add a markup to underlying LLM costs. Browser/runtime usage, model-heavy judgment steps and concurrency still affect total workflow economics, so a deployed agent count by itself is not enough to estimate production cost.

05

Cost and runtime controls

Airtop documents costThresholdCredits for limiting AI-call spend and timeThresholdSeconds for limiting runtime. These controls are useful when workflows include open-ended model reasoning or can encounter unexpectedly slow pages.

06

Which Airtop plan fits your workflow?

Use Free to validate one automation, Starter when you need several deployed agents but low concurrency, Professional when many workflows must run in parallel, and Enterprise when you need a much larger fleet, higher simultaneous-session capacity and enterprise support or compliance features.

Before upgrading, estimate monthly runs, peak simultaneous sessions, number of deployed workflows and how many steps require AI judgment. Then run a representative workflow and inspect actual credit usage. That measurement is more useful than extrapolating a generic vendor benchmark across every automation.

Sources

Primary and supporting sources

Facts were rechecked against the linked sources immediately before publication. Pricing, product availability and rollout status can change.

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