What this calculator does
Core Web Vitals are the three page-experience metrics Google publishes thresholds for: Largest Contentful Paint (LCP, loading speed), Interaction to Next Paint (INP, responsiveness) and Cumulative Layout Shift (CLS, visual stability). Each is rated Good, Needs Improvement or Poor against Google's own published cut-offs.
These thresholds come directly from Google and are used as a factor in how pages are evaluated for the page-experience side of search, alongside relevance. They are also simply useful on their own terms: a page that loads fast, responds quickly and does not jump around while loading is a better experience for anyone visiting it.
The formula
Each metric is compared against Google's published Good and Poor cut-offs: LCP good at 2.5 seconds or under, poor above 4 seconds; INP good at 200 milliseconds or under, poor above 500 milliseconds; CLS good at 0.1 or under, poor above 0.25. Anything between Good and Poor is rated Needs Improvement.
| Term | Meaning |
|---|---|
| LCP | Largest Contentful Paint: how long the largest visible element takes to render, in seconds. |
| INP | Interaction to Next Paint: how quickly the page responds to user interactions, in milliseconds. |
| CLS | Cumulative Layout Shift: a unitless score for how much visible content moves around unexpectedly while the page loads. |
The inputs explained
| Field | What to enter |
|---|---|
| Largest Contentful Paint (LCP) (s) | The LCP value for the page, in seconds, typically taken from a field or lab tool such as PageSpeed Insights. |
| Interaction to Next Paint (INP) (ms) | The INP value for the page, in milliseconds. |
| Cumulative Layout Shift (CLS) | The CLS score for the page, a small decimal such as 0.05 or 0.15. |
When to use it
Checking a page after a redesign
Running the new page's measured metrics through the same three thresholds shows whether a redesign improved, held steady, or worsened the page experience.
Prioritising performance work
Seeing which of the three metrics rates Poor, rather than treating "performance" as one vague problem, points directly at whether the issue is loading speed, responsiveness or layout stability.
Reporting page health over time
Recording the rating for each metric at intervals turns ongoing performance monitoring into a simple three-way traffic light rather than three raw numbers that are harder to communicate.
Worked examples
Every figure in the tables below is produced by this page’s own calculator at build time, so the numbers and the tool always agree. Select any row to load that scenario.
How the LCP rating changes across a range of load times
A fixed Good INP and CLS, against a range of LCP values.
| LCP | LCP rating | Overall assessment |
|---|---|---|
| 1.5s | Good (1.50s) | Good on all three metrics |
| 2.5s | Good (2.50s) | Good on all three metrics |
| 3s | Needs Improvement (3.00s) | At least one metric needs improvement |
| 3.5s | Needs Improvement (3.50s) | At least one metric needs improvement |
| 4s | Needs Improvement (4.00s) | At least one metric needs improvement |
| 5s | Poor (5.00s) | At least one metric rates Poor |
Questions
Can these thresholds change?
Yes. Google has revised the specific Core Web Vitals metrics and their thresholds before, replacing First Input Delay with Interaction to Next Paint in 2024, so the exact cut-offs used here reflect the currently published guidance rather than a permanent standard.
Do I need all three metrics to be Good?
That is the target for a page to be classed as having a good overall page experience under Google's framework, but each metric can still be worked on independently, and improving one does not require the others to already be Good.
Where do I get real LCP, INP and CLS numbers for my page?
Field data (from real visitors) is available through the Chrome User Experience Report and Google Search Console; lab data (from a simulated test) is available through tools such as PageSpeed Insights and Lighthouse.
Why does my lab score differ from my field score?
Lab tools measure a single simulated visit under controlled conditions, while field data reflects real visitors on real devices and connections, which vary far more and often show worse results, especially for INP.
For a related technical-SEO check on page weight, see the text-to-HTML ratio calculator.