LCP, CLS, and INP against Google's thresholds
The exact three metrics Google's ranking systems use to judge loading, stability, and responsiveness - tested against the official thresholds, honestly labeled as lab or field data.
Test my Core Web VitalsThe official thresholds
| Metric | Good | Needs improvement | Poor |
|---|---|---|---|
| LCP Largest Contentful Paint | < 2.5s | 2.5s - 4s | > 4s |
| CLS Cumulative Layout Shift | < 0.1 | 0.1 - 0.25 | > 0.25 |
| INP Interaction to Next Paint | < 200ms | 200ms - 500ms | > 500ms |
Lab vs. field, stated plainly
LCP and CLS are measured directly in a controlled lab run - repeatable, available every time.
INP is field-only by nature. Total Blocking Time (TBT) stands in as the lab proxy; real INP field data, when available, comes from a PageSpeed Insights (CrUX) fallback layer.
Good
Needs work
Poor
Frequently asked questions
What are the three Core Web Vitals?
LCP (Largest Contentful Paint) measures loading speed, CLS (Cumulative Layout Shift) measures visual stability, and INP (Interaction to Next Paint) measures responsiveness to user input. Google uses all three as ranking signals.
Why can't this tool measure INP directly?
INP is a field metric - it requires real user interactions over time, which only Chrome's own field data (CrUX) can capture. A lab test like this one measures Total Blocking Time (TBT) as the closest lab-available proxy for interaction responsiveness. When available, a PageSpeed Insights fallback can surface real CrUX field data for INP alongside the lab results.
What's the difference between lab and field data?
Lab data is a single controlled test run under fixed conditions - repeatable, but not necessarily representative of every real visitor. Field data is aggregated from real Chrome users who actually visited your site, capturing the range of devices and networks they used. Both are useful; they answer different questions.
Do I need to pass all three to rank well?
Core Web Vitals are one ranking signal among many, not a pass/fail gate. That said, poor scores - especially LCP and CLS - correlate with worse user experience regardless of ranking impact, so they're worth fixing on their own merits.
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LCP, CLS, and INP against Google's thresholds, honestly labeled.
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