Frameworks performance

How JavaScript frameworks score across LCP, INP and CLS.

Field data PhoneDesktopAll Scope All sites October 2026 edition · All devices field outcomes
Metric LCP INP CLS FCP TTFB
1

At a glance the headline numbers for Frameworks performance

How JavaScript frameworks score across LCP, INP and CLS.

92.5%
Best: Gatsby
good FCP
73.1%
Most used: jQuery
good FCP
70.6%
Worst: Vue
good FCP

Gatsby passes FCP most often of any framework. 92.5% of its sites pass. Vue passes least at 70.6%. jQuery (the most-used framework) sits at 73.1%. The gap is 22 percentage points.

The State of Web Vitals · October 2026 · 212,308 crawled sites · all devices field datacorewebvitals.io/state-of-cwv
2

The ranking sorted by FCP at p75, fastest first

# Framework FCP p75 Passing Sites
1 Gatsby 1.4s 92.5%
218
2 htmx 1.5s 83.0%
305
3 React 1.5s 81.2%
9,658
4 Next.js 1.5s 84.3%
1,840
5 Alpine.js 1.6s 82.4%
2,689
6 Svelte 1.6s 81.9%
471
7 Remix 1.6s 81.1%
53
8 jQuery 1.9s 73.1%
144,465
9 Nuxt 1.9s 72.6%
1,311
10 Vue 2.0s 70.6%
12,199
11 Angular 2.0s 70.0%
3,396
The State of Web Vitals · October 2026 · 212,308 crawled sites · all devices field datacorewebvitals.io/state-of-cwv
3

Passing FCP per framework which group passes the FCP most often

FrameworkSitesPassing FCPp75
Gatsby 0.1% 218 93% 1.4s
Next.js 0.9% 1,840 84% 1.5s
htmx 0.1% 305 83% 1.5s
Alpine.js 1.3% 2,689 82% 1.6s
Svelte 0.2% 471 82% 1.6s
React 4.7% 9,658 81% 1.5s
Remix 0% 53 81% 1.6s
jQuery 69.6% 144,465 73% 1.9s
Nuxt 0.6% 1,311 73% 1.9s
Vue 5.9% 12,199 71% 2.0s
Angular 1.6% 3,396 70% 2.0s
Good Needs Improvement Poor Sorted best-passing first · median colored by its own rating · pass = good FCP (1.8s at p75) · one value per site

93% of Gatsby sites pass FCP. Angular trails 23 points behind, leaving 30% of its sites failing. computed

The State of Web Vitals · October 2026 · 212,308 crawled sites · all devices 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 69.6%
812.3s
97104ms
880.04
731.9s
511.4s
Vue 5.9%
762.4s
95127ms
830.06
712.0s
521.4s
React 4.7%
852.1s
95103ms
920.01
811.5s
671.1s
Angular 1.6%
662.9s
88162ms
570.24
702.0s
76768ms
Alpine.js 1.3%
891.9s
97115ms
910.03
821.6s
571.1s
Next.js 0.9%
852.1s
68233ms
660.17
841.5s
69880ms
Nuxt 0.6%
722.6s
88158ms
690.14
731.9s
631.0s
Svelte 0.2%
832.1s
92138ms
860.05
821.6s
71885ms
htmx 0.1%
911.9s
99108ms
870.03
831.5s
581.1s
Gatsby 0.1%
712.6s
82180ms
650.19
931.4s
78755ms
Remix 0%
852.2s
87150ms
730.11
811.6s
561.1s
60%95%+ passing Cell: pass rate, small number = p75 · faded rows: under 100 sites

One row per framework, 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.

Gatsby leads on FCP: 93% of its sites pass. Angular trails at 70%. computed

The State of Web Vitals · October 2026 · 212,308 crawled sites · all devices field datacorewebvitals.io/state-of-cwv
5

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

A JavaScript framework shapes how much code runs in the browser to put your page on the screen. Some render on the server and ship light; others send a large bundle and rebuild the page on the client, which lands on the main thread and shows up in INP. The framework is not destiny, but its defaults and how you use them decide how much JavaScript the visitor has to pay for.

Start by looking at what ships to the browser and when it runs. Render on the server where you can, split the bundle so each page only loads what it needs, and defer the work that is not required for the first interaction. Framework JavaScript runs on the main thread, so the less of it the browser has to execute, the better INP gets.

How does your framework affect Core Web Vitals?

Among the JavaScript frameworks, Gatsby reaches a good FCP on 92.5% of sites; Angular on 70.0%.

Related signals CDN (7) → CMS (12) → 212,308 crawled sites with Chrome field data, representing millions of real page loads · How we measured