Tools / VEO-Av1an Bridge
VEO-Av1an Bridge
An open-source video compressor that analyses footage scene by scene and gives each section only the bitrate it needs — smaller files without visible quality loss.
v1.0.0FreeOpen source · MIT11 October 2026

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macOS — Apple Silicon (M1–M5)41 MB
Self-contained app; only ffmpeg/ffprobe must be installed on the system.
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macOS — Intel18 MB
Install ffmpeg and mkvtoolnix via Homebrew (see KURULUM-INTEL.txt in the package). Not yet tested end to end.
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Windows 10/11 (64-bit)214 MB
Command-line tool; requires Python 3. All encoders are bundled (see WINDOWS-KURULUM.txt).
VEO-Av1an Bridge is free and open source under the MIT licence, provided as is, without warranty of any kind. Keep the originals of the videos you compress.
Source code (GitHub) ↗Release notes ↗Related article: 56 MB to 3 MB: Shrinking Video Without Losing Quality, for Free
What it does
VEO-Av1an Bridge chains two open-source projects into a single command:
- VEO (Video Encoding Optimizer) runs trial encodes scene by scene and finds, for each section, the lowest bitrate that still meets the target quality.
- Av1an splits the video into chunks, encodes them in parallel on all CPU cores, applies VEO’s per-scene quality settings (zones) and joins the result into one file.
No new codec is involved — the output is standard AV1, H.264 or H.265. The saving comes from distributing the bit budget per scene. In our test, a 56 MB video came out at 3 MB.
Installation
- macOS: Unzip and drag the app into Applications. The app is unsigned, so on first launch use right-click › Open. The interface is in English and Turkish (follows the system language); output can be
.mp4or.mkv. - Windows: Python 3 must be installed. Add the bundled
tools\folder to PATH or run from inside it. A SmartScreen warning is expected because the package is unsigned. Example:python bridge.py --input video.mp4 --output out.mp4 --encoder svt-av1
Known limitations
- 4:4:4 pixel formats and odd-numbered dimensions have limited support; yuv420p with even dimensions is recommended.
- Tested on Apple Silicon. If you run it on another platform, let us know how it goes — issues can be reported on GitHub.