AVQT, Apple's Advanced Video Quality Tool, introduced at WWDC 2021, is a perceptual full-reference metric that estimates the quality of a compressed video on a 1-to-5 scale mirroring a Mean Opinion Score, reporting both per-frame and per-segment scores. Like VMAF and PSNR it takes the source and the compressed file, but two things set it apart. First, it is viewing-setup aware: it accepts display size, resolution, and viewing distance as explicit inputs and adjusts the predicted quality for how a real viewer in that setup would perceive the artifacts, so the same encode scores higher as the viewer sits farther away — a knob VMAF lacks. Second, it is fast and format-rich, built on AVFoundation and Metal (around 175 fps on 1080p) with native HDR10, HLG, and Dolby Vision handling. The catches are practical: AVQT runs only on macOS, which complicates Linux CI pipelines, and it is closed-source with no published model, so you cannot inspect or customize how a score was reached.
The handbook · 7 volumes
Fora Soft Video Engineering Handbook
AVQT is Apple's full-reference perceptual metric, and its scores need to be read against VMAF and PSNR before they drive encoding decisions. We wrote seven volumes covering the whole video stack, and for AVQT start with Volume 1: perceptual quality metrics, full-reference measurement, H.264, HEVC and AV1 encoding, with Volume 3 on adaptive streaming and players. Written by Nikolay Sapunov, CEO at Fora Soft.
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