A repeatable experiment plan for animation, images, fonts, and page loading, with an honest results template.
No before-and-after benchmark is published here yet. This page provides a measurement protocol and results worksheet; it does not claim a score, frame rate, or speed improvement for AVRXT.
Record the source revision, page, browser version, physical device, viewport, network conditions, and cache state. Use the same interaction in each run. A narrow desktop viewport is useful for layout testing but does not reproduce a phone’s CPU, memory, touch input, or thermal limits.
Transfer size, rendering delay, reserved layout space
Fonts
Compare loading and fallback strategy
Text visibility and movement during loading
Page loading
Remove one unnecessary resource
Request waterfall and critical rendering path
For web experience, distinguish loading, responsiveness, and visual stability. Core Web Vitals cover those concerns through LCP, INP, and CLS. Lab results and real-user data answer different questions; one local run is not a field-performance claim. See Google’s Web Vitals guide.
Use the browser’s performance tooling to record a repeatable sequence: load the page, wait for the same content state, scroll to the artwork, interact with it, then submit a non-mutating test interaction where available. Run several comparable trials and keep raw traces locally. Do not record private pages or real email submissions just to collect a trace.
Change one variable and repeat the sequence. Report the number of runs, spread, and environmental differences rather than selecting the best result. Check visual quality and accessibility after an optimization. Pausing offscreen decoration can help, but observation APIs and composited effects still need profiling in the actual page.
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