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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteThe figures 2.2 ms, 19.9 ms and 529 ms are not three scores for one universal A/B testing runtime speed. They are ABTestly’s reported 75th-percentile times for one event—the moment a variation lands in the DOM—in three different navigation and cache conditions. The measurements are useful as a description of that test, but they do not establish how quickly every experiment will appear to real visitors.
What the three figures measure
In a September 26, 2026 post, ABTestly reported timing 200 page loads per condition in headless Chromium. Its endpoint was the time from navigation start until a variation landed in the DOM. The test used the built runtime and a single variation that rewrote an above-the-fold heading.
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| Condition | ABTestly-reported p75 | What the condition means |
|---|---|---|
| Single-page app route change | 2.2 ms | A route changed within a single-page application. |
| Repeat view, warm cache | 19.9 ms | A repeat page view with cached resources. |
| First visit, empty cache, throttled | 529 ms | A first view with an empty cache, tested at 1.6 Mbps downstream and a 150 ms round trip. |
These are the vendor’s observations, not independently replicated results. The large spread reflects distinct test conditions; it is not a like-for-like ranking of three runtimes or three versions of the same page load. ABTestly’s post describes the setup and results.
DOM arrival is not the same as what visitors see
The benchmark’s endpoint is a DOM change, not a measurement of when a visitor first sees the variation. In the throttled first-visit condition, ABTestly says the original heading appeared on screen before replacement in all 200 loads, with a median delay of 326 ms before it was replaced. On cached repeat views, the original was absent from every painted frame in 199 of 200 loads; on route changes, it was absent in all loads, according to the post.
#1 Best Overall
That distinction matters: a variation can land in the DOM quickly after navigation and still follow an initial paint of the original content. The reported median is specific to this heading rewrite and throttled condition; it does not establish the amount of flicker on other pages or with more complex variations.
Why 529 ms is not a real-world first-visit estimate
ABTestly says the benchmark ran against a local origin. The stated network throttle applied, but the test did not include real first-visit DNS lookup, TLS setup or edge latency. The processor was not throttled either. ABTestly describes 529 ms as a floor rather than a field result and says a first visit on a mid-range phone would be slower. The post does not provide evidence quantifying how much slower.
The scope is also narrow: one browser setup, one heading rewrite and one local-origin benchmark. The result does not establish timing across other browsers, devices, network conditions, page structures or variation complexity. Nor is this endpoint a page-load metric.
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Use LCP as complementary context, not a substitute
Largest Contentful Paint (LCP) measures when the largest visible image, text block or video is rendered relative to navigation. It is different from timing when a variation enters the DOM. web.dev’s LCP guidance recommends evaluating the 75th percentile of page loads separately for mobile and desktop, with 2.5 seconds or less considered a good LCP target. It also notes that connection setup, redirects and time to first byte can materially affect field measurements.
That guidance helps put page experience in context; it does not validate or contradict ABTestly’s runtime figures. A runtime benchmark and field LCP answer different questions and should not be presented as interchangeable scores.
The anti-flicker tradeoff
ABTestly says its runtime loads as a dynamic script and does not block the page parser. Its optional anti-flicker mechanism hides the page using an opacity rule until variants apply or a two-second timeout expires; the setting is unchecked by default.
The vendor’s rationale is that page-wide hiding affects visitors who are not assigned to an experiment and could leave a page visibly empty while configuration is slow, whereas flicker is limited to pages actually changed by a variant. This is ABTestly’s design rationale, not an independently tested comparison showing which approach produces a better visitor experience.
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ABTestly’s dashboard flags a variation as slower when its p75 LCP is at least 400 ms above the control. A row is evaluated only after passing these checks, stopping at the first failure:
- Capture rate is not above 100%.
- Each arm has at least 100 page loads.
- The capture-rate gap between arms is no more than 20 percentage points.
- Capture is at least 50% in each arm.
ABTestly explicitly characterizes this as a descriptive, not inferential, measure: “There is no confidence interval, no bootstrap, and no significance test. The panel is a descriptive guardrail, not an inferential one.” The vendor also warns that a 400 ms difference based on 100 loads per arm is not equivalent evidence to the same difference based on 100,000. Although the panel shows load counts, it does not weight the evidence for the reader.
The panel makes no correction across devices or variations. In ABTestly’s example, four variants across two devices create six comparisons, each judged against its own threshold. A result marked “not flagged” therefore means there was no visible threshold crossing at the displayed volume—not that the variation has been proved safe or that the difference is statistically reliable.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Questions to ask when evaluating a runtime benchmark
When a vendor shares a speed figure, ask for the measurement details that determine what it means:
- Endpoint: Is the clock stopping when a variant enters the DOM, when it is painted, or at a page-level metric such as LCP?
- Navigation and cache: Are route changes, warm-cache repeat views and uncached first visits reported separately?
- Test environment: Was the origin local or deployed? Were network and processor both constrained? Which browser, device and page were used?
- Visible behavior: How often did original content paint before the variation, and for how long?
- Evidence behind flags: What are the load counts and capture rates for each arm? Does the tool report uncertainty, and how does it handle multiple device and variation comparisons?
These questions make it possible to distinguish a useful, bounded benchmark from a claim about general visitor experience. The specific figures here should be read within ABTestly’s stated test conditions and limitations.
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