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Operating System Market Share

Real-time OS usage statistics across desktop, mobile, and tablet

NetMarketShare tracks operating system market share worldwide using real human visitor data, with bots and fraudulent traffic filtered out so the numbers reflect the platforms people are actually using to browse the web.


What is operating system market share?

Operating system market share — sometimes called OS usage share — is the percentage of web traffic generated by each operating system within a given time period. It is the standard measure of which platforms people are running, and is used by software vendors, IT teams, ad networks, and analysts to decide which operating systems to support, test, and target.

Desktop operating systems we track

  • Microsoft Windows — the dominant desktop OS (Windows 11, Windows 10, and earlier versions)
  • Apple macOS — the operating system for Mac desktops and laptops
  • Linux — including Ubuntu, Fedora, Debian and other distributions
  • ChromeOS — Google's web-first OS for Chromebooks

Mobile and tablet operating systems we track

  • Google Android — the dominant mobile OS worldwide, across phones and tablets
  • Apple iOS — the operating system for iPhone
  • Apple iPadOS — tracked separately from iOS since September 2019

OS market share by device type

Operating system usage looks completely different on desktop vs. mobile — Windows dominates desktop while Android and iOS dominate mobile. View segmented reports:

Related market share reports


How is OS market share measured?

NetMarketShare measures operating system usage from real visitor sessions across our partner network, filtering out bot traffic, datacenter traffic, and other non-human sources. The result is OS statistics that reflect actual users, not automated noise.

Read about our methodology · How we detect and remove invalid traffic

Why accurate OS market share matters

Operating system share data drives real engineering decisions: which OS versions QA teams test against, which platform APIs developers can safely depend on, which devices ad networks optimize creative for, and where product teams invest support effort. Inflated or bot-skewed numbers lead to wasted work supporting platforms no real users have, or skipping platforms real users actually depend on.