Open-source Mac app that runs EmbeddingGemma 2 locally to search your files by what’s in them
DigUp is a free, open-source Mac app that uses Google DeepMind's EmbeddingGemma 2 model to search local files, including text, images, audio, and video. It runs locally using ggml-org's Q8_0 GGUF on llama.cpp with Metal, within a native Swift app. The app indexes files, peaking under 2 GB, and allows users to search by describing content, with results appearing quickly after typing. It only connects online for initial model download and optional updates.
Time & source
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PublishedOffset at this time: UTC+0Oct 10, 2026, 12:43 UTC
IngestedOffset at this time: UTC+0Oct 10, 2026, 14:00 UTC
- Published
- Oct 10, 2026, 12:43
- Ingested
- Oct 10, 2026, 14:00
- Source type
- Dev community
- Tier
- Community
- Source status
- Healthy
Tier is a per-source editorial setting, not a per-item score.
DigUp is a free Mac app that runs Google DeepMind’s new EmbeddingGemma 2 locally over your own files. The model puts text, images, audio and video in one space, so you describe what you remember and land on it:
- “a dog on the beach” finds the photo, and the same search in Bengali or Arabic finds it too
It’s ggml-org’s Q8_0 GGUF (865 MB, downloaded once) on llama.cpp with Metal, inside a native Swift app; no Python. Searching loads only the text encoder (~250 MB) and shows results about a tenth of a second after you stop typing. Indexing peaks under 2 GB, and the helper exits when it’s done. Audio and video of any length go in as 30 s windows and a frame per shot. Everything runs locally; it goes online only for the model download and an update check you can turn off.