JS libraries impact

Performance impact by framework provider.

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

At a glance the headline numbers for JS libraries impact

Performance impact by framework provider.

20
Providers ranked
After min-sites filter
142,710
Sites in sample
Combined across all items
0.03
Best CLS (p75)
Turbo/Hotwire
The State of Web Vitals · Q1 2026 · 94,910 sites · desktop field datacorewebvitals.io/state-of-cwv
2

The ranking sorted by CLS at p75, fastest first

# Provider CLS p75 Passing Sites
1 Turbo/Hotwire 0.03 92.6%
258
2 Flickity 0.07 81.7%
2,891
3 Stimulus/Hotwire 0.08 83.8%
1,536
4 GSAP 0.08 81.8%
2,573
5 jQuery 0.09 77.9%
67,906
6 Swiper 0.09 78.5%
15,692
7 Next.js 0.10 75.1%
2,085
8 Lazysizes 0.10 76.1%
6,844
9 Lit 0.11 73.6%
5,243
10 Ionic 0.12 68.4%
116
11 Lodash 0.12 72.4%
13,200
12 Slick Carousel 0.12 72.1%
7,462
13 Moment.js 0.12 71.9%
4,065
14 Vue.js 0.12 71.9%
5,677
15 Backbone.js 0.13 72.0%
818
16 Owl Carousel 0.13 68.8%
4,359
17 Ember.js 0.15 71.8%
67
18 Nuxt 0.16 65.3%
647
19 React 0.19 58.6%
235
20 Angular 0.33 43.9%
1,036
The State of Web Vitals · Q1 2026 · 94,910 sites · desktop field datacorewebvitals.io/state-of-cwv
3

Passing CLS per provider which group passes the CLS most often

ProviderSitesPassing CLSp75
Marko 0% 12 100% 0.01
Turbo/Hotwire 0.3% 258 93% 0.03
Stimulus/Hotwire 1.6% 1,536 84% 0.08
GSAP 2.7% 2,573 82% 0.08
Flickity 3% 2,891 82% 0.07
Polyfill.io 0% 46 79% 0.09
Swiper 16.5% 15,692 79% 0.09
jQuery 71.5% 67,906 78% 0.09
lazysizes 7.2% 6,844 76% 0.10
Next.js 2.2% 2,085 75% 0.10
Lit 5.5% 5,243 74% 0.11
Lodash 13.9% 13,200 72% 0.12
Slick Carousel 7.9% 7,462 72% 0.12
Backbone.js 0.9% 818 72% 0.13
Moment.js 4.3% 4,065 72% 0.12
Vue.js 6% 5,677 72% 0.12
Ember.js 0.1% 67 72% 0.15
Owl Carousel 4.6% 4,359 69% 0.13
Ionic 0.1% 116 68% 0.12
Nuxt.js 0.7% 647 65% 0.16
React 0.2% 235 59% 0.19
Angular 1.1% 1,036 44% 0.33
Good Needs Improvement Poor Sorted best-passing first · median colored by its own rating · pass = good CLS (0.1 at p75) · one value per site

93% of Turbo/Hotwire sites pass CLS. Angular trails 49 points behind, leaving 56% of its sites failing. computed

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

All five vitals at once the whole category without toggling - cell is the pass rate, small number the p75

LCP
INP
CLS
FCP
TTFB
jQuery 71.5%
852.0s
9962ms
780.09
801.6s
571.2s
Swiper 16.5%
822.2s
9967ms
790.09
771.7s
521.4s
Lodash 13.9%
782.4s
9869ms
720.12
731.9s
511.4s
Slick Carousel 7.9%
862.0s
9964ms
720.12
811.6s
551.2s
lazysizes 7.2%
862.1s
9967ms
760.10
811.6s
571.2s
Vue.js 6%
832.1s
9976ms
720.12
811.6s
611.1s
Lit 5.5%
842.1s
9975ms
740.11
811.6s
641.0s
Owl Carousel 4.6%
842.1s
9962ms
690.13
801.6s
521.3s
Moment.js 4.3%
802.2s
9966ms
720.12
761.7s
571.3s
Flickity 3%
882.0s
10067ms
820.07
841.5s
651.1s
GSAP 2.7%
792.3s
10065ms
820.08
761.7s
521.4s
Next.js 2.2%
862.0s
95106ms
750.10
881.4s
76773ms
Stimulus/Hotwire 1.6%
941.8s
9969ms
840.08
921.3s
81706ms
Angular 1.1%
702.7s
97111ms
440.33
791.7s
85539ms
Backbone.js 0.9%
742.5s
9967ms
720.13
682.0s
461.5s
Nuxt.js 0.7%
762.5s
98100ms
650.16
781.7s
641.0s
Turbo/Hotwire 0.3%
961.4s
9980ms
930.03
931.1s
83692ms
React 0.2%
812.1s
91111ms
590.19
841.6s
651.1s
Ionic 0.1%
613.1s
94106ms
680.12
582.2s
671.3s
Ember.js 0.1%
802.3s
9782ms
720.15
731.9s
68945ms
Polyfill.io 0%
782.1s
10074ms
790.09
841.4s
69889ms
Marko 0%
912.2s
10071ms
1000.01
551.9s
01.5s
60%95%+ passing Cell: pass rate, small number = p75 · faded rows: under 100 sites

One row per provider, one column per vital - the cell is the share of sites passing, the small number the p75. No toggling needed to see where the category actually differs.

Turbo/Hotwire leads on CLS: 93% of its sites pass. Angular trails at 44%. computed

The State of Web Vitals · Q1 2026 · 94,910 sites · desktop field datacorewebvitals.io/state-of-cwv
Related signals A/B testing (10) → Personalization (5) → E-commerce (14) → CDN (15) → Chrome field data from 94,910 sites, representing millions of real page loads · How we measured