Scheduling API use
How the page schedules main-thread work: scheduler.yield / postTask vs setTimeout churn.
At a glance the headline numbers for Scheduling API use
How the page schedules main-thread work: scheduler.yield / postTask vs setTimeout churn.
2.1% of scheduling calls use scheduler.yield. 47.3% chunk work with setTimeout.
The scheduling API use mix who uses what, and how fast each group loads
Scheduling API use. On the fleet: 47.3% settimeout, 46.4% raf, 3.4% requestidlecallback. 96.9% of sites use at least one setTimeout.
Lowest-share bucket: INP 46ms. Highest-share bucket: INP 49ms. r = +0.50.
By count setTimeout leads (47.3%); by bytes it is scheduler yield (0.0%). computed
Passing INP per bucket every category and count level at once - color is the pass rate
Each row is a category, each column its own count bucket (few on the left, many on the right); the cell is the share of those sites passing INP.
No category moves the INP pass rate much, however many a site ships. computed
Few vs many - does quantity cost INP? the pass rate with few vs many of each category
Per category: the pass rate among pages with FEW of it (hollow ring) against pages with MANY (solid dot), worst trend first. Thin buckets are excluded from the endpoints.
More SetTimeout costs the most: the INP pass rate falls from 99% with few to 98% with many. computed
Why this matters for the Core Web Vitals, and where to start fixing it
Long tasks block every interaction that arrives while they run. The fix is yielding: split the work and give the browser a chance to handle input in between. How a site yields matters. scheduler.yield hands control back and resumes with priority. postTask schedules work with an explicit priority. A setTimeout chain yields too, but blindly: no priority, and every link in the chain adds delay.
Seeing the modern scheduler APIs on a site is a strong signal: someone engineered the INP instead of inheriting it.
How does this affect the Core Web Vitals?
Passing INP barely moves across the range: 99% at one end, 98% at the other. This signal does not separate passing sites from failing ones.
The split is bigger on CLS: 83% pass where SetInterval is rare, 76% where it is common.
Chrome field data from 189,915 sites, representing millions of real page loads. How we measured.