# Install libvmaf with Homebrew Perceptual video quality assessment based on multi-method fusion. Version 3.2.0 via Homebrew; verified from local package data. ## Install ```sh sudo av install brew:libvmaf ``` Additional install commands: ### macOS - Homebrew (100%): ```sh brew install libvmaf ``` Evidence: provider-native install command ## Package facts - **Package key:** brew:libvmaf - **Package manager:** Homebrew - **Version:** 3.2.0 - **Source summary:** Perceptual video quality assessment based on multi-method fusion - **Homepage:** - **Repository:** - **Generated:** 2026-08-03T00:40:33+00:00 ## Executables - vmaf (alias) ## Install behavior - Bottle: not available ## Freshness - Page generated: 2026-08-03 - Package-manager version: 3.2.0 ## Project history and usage VMAF, packaged by Homebrew as libvmaf, is Netflix's open-source implementation of Video Multi-Method Assessment Fusion, a perceptual video-quality metric for comparing encoded video against a reference. The package matters because it turns a research metric into a command-line tool, C library, Python tooling, and FFmpeg-integrated workflow used by video engineers rather than only by researchers. ### Project history Netflix developed VMAF to better predict viewer-perceived streaming video quality than simple signal metrics such as PSNR. Netflix's own reference list traces VMAF through earlier academic work on fusion-based video quality assessment and notes that the project was open-sourced on GitHub in June 2016. The first public implementation combined a C feature-extraction core with Python control code for experimentation. By October 2018 Netflix described the addition of a standalone executable, AVX acceleration in December 2016, frame-level multithreading in June 2018, and the packaging of the implementation as libvmaf with help from the FFmpeg community. ### Adoption history VMAF became part of practical codec evaluation because Netflix used it for production encoding decisions, Dynamic Optimizer workflows, and A/B experimentation around video quality. The GitHub README also documents FFmpeg support through configure --enable-libvmaf and AOM common test-condition usage, which made the library a package-manager staple for video-toolchain builds. ### How it is used Package users install libvmaf to run the vmaf command, link the C library into quality-analysis tools, train or test models with the Python layer, or enable FFmpeg's libvmaf filter. It is especially useful when comparing encoders, bitrates, resolutions, or codec changes on a perceptual scale. ### Why package nerds care For package nerds, libvmaf is the quality-metric dependency that turns FFmpeg from a transcoder into a measurable codec lab. Its presence in package managers signals a mature media stack: SIMD-heavy native code, model files, Python tooling, and a bridge between academic video-quality research and production streaming workflows. ### Timeline - 2014-2015: Academic work on fusion-based and ensemble-learning video quality metrics appears in the VMAF reference list. - 2016-06: Netflix open-sources VMAF on GitHub. - 2016-12: Netflix adds AVX optimization to VMAF's convolution work. - 2018-06: Frame-level multithreading and frame skipping make practical high-resolution runs faster. - 2018-10-25: Netflix describes libvmaf packaging and FFmpeg filter adoption in a VMAF project update. - 2020-12-03: libvmaf v2.0.0 is released with a new optimized implementation and API. - 2023-12-07: libvmaf v3.0.0 removes APIs deprecated in v2.0.0. - 2026-06: Netflix announces VMAF model v1 documentation and model-selection guidance. ### Related projects - VMAF is closely related to FFmpeg, AOM codec test conditions, Netflix's Dynamic Optimizer work, CAMBI for banding detection, and traditional objective metrics such as PSNR, SSIM, MS-SSIM, and PSNR-HVS that are also exposed by the package. ### Sources - - - - ## Security Notes broad file, network, media, or database tool signal. - **Geiger risk:** blue / medium - broad file, network, media, or database tool signal ## Combined YAML source View the package source record on GitHub. [combined/libvmaf.yml](https://github.com/automic-vault/db/blob/main/combined/libvmaf.yml) ## Sources - Nucleus package database - Geiger risk classifier - curated package history - pkgdb category and tag curation