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.
时间与来源
时间显示为 UTC
显示时区：UTC
本地时区尚不可用，暂时显示 UTC。
发布当时偏移：UTC+02026年10月10日 12:43 UTC
收录当时偏移：UTC+02026年10月10日 14:00 UTC
- 发布
- 2026年10月10日 12:43
- 收录
- 2026年10月10日 14:00
- 来源类型
- 开发者社区
- 档位
- 社区
- 信源状态
- 同步延迟
档位是按信源手工设定的编辑判断，不是逐条打分。
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.