Local Desktop Search Tool Powered by EmbeddingGemma 2 and llama.cpp

X postXuan-Son NguyenTool

A desktop search utility shared on Reddit runs EmbeddingGemma 2 via llama.cpp to index and retrieve local files on macOS. Xuan-Son Nguyen highlighted the tool, calling it far superior to Apple's default Spotlight search.

Key points

  1. The tool uses EmbeddingGemma 2 alongside llama.cpp for local semantic search.
  2. According to Xuan-Son Nguyen, it performs significantly better than macOS Spotlight.
  3. The creator confirmed that Windows and Linux ports are currently in development.
  4. An opt-in code search feature allows users to jump directly to matching lines inside a code editor.

Why it matters

Running small embedding models locally brings semantic file search directly to the operating system without sending private data to cloud services. The project highlights the practicality of lightweight local inference via llama.cpp.

Analysis

Standard desktop search engines like Spotlight typically rely on exact keyword matches and metadata. Integrating local embedding models like EmbeddingGemma 2 allows users to perform conceptual queries completely offline with minimal resource overhead.

Original post

Xuan-Son Nguyen

@ngxson · 11 October 2026

Someone on Reddit made a searching app that runs on EmbeddingGemma 2 🤯 Much better than MacOS's default Spotlight 🔥 t.co/pT0qex0OgE

2.8k likes58 replies2.3k bookmarks260.3k views

View on X
More posts in the thread (2)
  1. t.co/dEe3yuO27J
  2. @_ARahim_ Cool project! Great use of llama.cpp too 😁
Selected replies (5)
  • @_ARahim_ @ngxson That was me, thanks for sharing it. t.co/9Amgb3KqZC
  • @Fanfulladev @ngxson Searching your own videos by describing the scene, fully offline, should be built into every OS
  • @_ARahim_ @ngxson Thank you. Currently working on windows and Linux port.
  • @GlennCameronjr @ngxson EmbeddingGemma 2 is a real cool model. You can build so many things with it.
  • @Hft_freedom @ngxson @raycast mate

Mentioned links

Summary generated by AI (Gemini 3.8 Flash, 12 October 2026). It may contain errors – the original source is authoritative.

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