Why it matters
Google's Core Web Vitals assessment uses the 75th percentile of real users' visits, not an average and not a lab test. If you collect your own field data with the web-vitals library or an analytics tool, you need to compute that percentile the same way to know where you stand.
This calculator does that, rates each metric against the official thresholds and charts the distribution. It also computes CLS from raw layout-shift entries using the session-window rule, which is where most hand-rolled CLS numbers go wrong.
How it works
- InputLCP, INP and CLS values or a CSV
- In your browser75th percentile against Google's thresholds
- OutputRatings, a distribution and a CLS calculator
Where it fits in a designer's workflow
- Plan
- Design
- Build
- Test
- Launch
By the numbers
Show the numbers as a table
| Metric | Visits | 75th percentile | Rating | Good | Needs improvement | Poor |
|---|---|---|---|---|---|---|
| LCP | 60 | 2,540 ms | needs improvement | 72% | 22% | 7% |
| INP | 60 | 165 ms | good | 83% | 17% | 0% |
| CLS | 60 | 0.063 | good | 85% | 15% | 0% |
How to use it
- Paste a CSV with lcp, inp and cls columns, or lines like 'LCP 2450'.
- Read the 75th percentile and rating for each metric.
- Look at the distribution to see the slow tail.
- Paste layout-shift entries to compute CLS.
FAQ
Why the 75th percentile?
So three quarters of visits must be good for a page to pass. It ignores a few outliers but not a slow minority.
What are the thresholds?
LCP good at 2.5 s or less, poor over 4 s. INP good at 200 ms or less, poor over 500 ms. CLS good at 0.1 or less, poor over 0.25.
What's a session window?
Layout shifts less than 1 second apart, in a window of at most 5 seconds. CLS is the largest window's total, not the sum of every shift.
Is my data uploaded?
No. It's processed in your browser.
