The State of Web Vitals

Total Blocking Time (lab)

Total Blocking Time on the lab crawl.

Field data PhoneDesktopAll Scope All sites Q1 2026 edition · Phone field outcomes
Metric LCP INP CLS
1

At a glance the headline numbers for Total Blocking Time (lab)

Total Blocking Time on the lab crawl.

20ms
on the typical site
half of sites sit at or below
189ms
1 in 4 sites exceed this
the top quarter
6.8s
the heaviest 1%
the long tail
94,910
sites measured
phone field data

The typical site blocks the main thread for 20ms during the lab load.

The State of Web Vitals · Q1 2026 · 94,910 sites · phone field datacorewebvitals.io/state-of-cwv
2

Distribution & median CLS site count and median CLS at each level of total Blocking Time (lab)

0.00 0.04 0.08 0.11 0.15
0.1
0 19195 38389
0 0.01–0.038 0.038–0.143 0.143–0.541 0.541–2.05 2.05–7.74 7.74–29.3 29.3–111 111–419 419–1585 1585–5994 >p98
Good (≤0.1) Needs improvement Poor (>0.25) Site count
The State of Web Vitals · Q1 2026 · 94,910 sites · phone field datacorewebvitals.io/state-of-cwv
3

Passing CLS by total Blocking Time (lab) which level passes the CLS most often

Total Blocking Time (lab)SitesPassing CLSCLS
0 38,389 92% 0.00
0.01–0.038 12 80% 0.00
0.038–0.143 74 89% 0.00
0.143–0.541 227 88% 0.00
0.541–2.05 925 89% 0.00
2.05–7.74 3,124 90% 0.00
7.74–29.3 7,534 89% 0.00
29.3–111 14,344 88% 0.00
111–419 15,446 86% 0.00
419–1585 9,921 85% 0.00
1585–5994 3,783 85% 0.00
>p98 1,131 84% 0.00
Good Needs Improvement Poor Faded rows: under 100 sites

Total Blocking Time (lab) 20ms. p75 189ms. p99 6.8s. Spearman with CLS r = +0.31. At the low end (0ms): CLS 0.00. At the high end (>p98): CLS 0.00. computed

The State of Web Vitals · Q1 2026 · 94,910 sites · phone field datacorewebvitals.io/state-of-cwv
4

Why this matters for the Core Web Vitals, and where to start fixing it

Total Blocking Time counts the parts of long tasks where a click would have waited. It is the lab stand-in for INP: a crawler does not click, so instead we measure how often the main thread was too busy to answer if someone had.

High TBT with good field INP usually means real visitors interact after the dust settles. The risk lives in the early click, the visitor who taps the menu while the tag pile is still booting. The fix list is the script list: less of it, later, in smaller pieces.

How does this affect the Core Web Vitals?

Blocking time correlates with the CLS. Where the blocking time is low, 92% of sites pass the CLS. Where it is high, 84% do. The decline is gradual. There is no point where sites suddenly start failing.

The effect is bigger on LCP. Where the blocking time is low, 88% of sites pass it. Where it is high, 72% do.

Go fix it Yield to the main thread → 14 methods to defer JavaScript → Interaction to Next Paint →
Related signals Main-thread CPU (lab) → Lab paint timeline → Document lifecycle (lab) → Chrome field data from 94,910 sites, representing millions of real page loads · How we measured