website/layouts/engines/list.html
Engines we build
Most LocalAI backends wrap somebody else's engine. These were written from scratch, each one because the thing we needed was a multi-gigabyte Python install, or closed, or nobody had built it yet. What ships instead is a binary and a GGUF file, checked against the reference implementation in CI, running on the machine you already own.
Install LocalAI →How backends work
0 Engines
0 Modalities
0 Python at inference
0 Licence
All {{ len $engines }} {{ range $cats }} {{ $n := len (where $engines "category" .id) }} {{ if gt $n 0 }}{{ .label }} {{ $n }} {{ end }} {{ end }} {{ range $cats }} {{ $inCat := where $engines "category" .id }} {{ if gt (len $inCat) 0 }}
{{ .label }}
{{ .blurb }}
{{ range $inCat }} {{ $e := . }} [ {{ with $e.media }}
{{ end }}
{{ $e.language }}{{ with $e.status }} {{ . }} {{ end }}
{{ $e.tagline }}
{{ with $e.highlights }} {{ range . }}- {{ . }} {{ end }} {{ end }} {{ with $e.clips }} {{ range . }} Video
{{ .caption }} {{ end }} {{ end }} {{ $e.name }} on GitHub ↗ ]({{%20$e.repo%20}}) {{ end }}
{{ end }} {{ end }}
Nothing in that modality yet.
The rule we hold them to
Every engine here is gated against the framework it replaces, on the same input, on the same machine. That means a transcript identical to the reference, boxes that land on the same pixels, or a waveform inside a stated tolerance. Speed work comes after that, and the numbers on this page come out of each engine's own benchmark suite.