Chat with a local AI, ask questions about your own documents, and keep everything on your computer. No cloud, no account, no telemetry.
Download · Source on GitHub · Website · Verified model catalog
HilbertRaum is an open-source desktop app (Windows, macOS, Linux; GPL-3.0-or-later) that runs open-weight
GGUF models with llama.cpp entirely on your machine. It ships document Q&A with citations, evidence
review, image understanding, Whisper transcription and dictation, offline translation for 51 languages,
and an optional OpenAI-compatible loopback API for other programs on the same computer.
The whole workspace is portable and encrypted: app, models and data can live on a USB stick or an external SSD and move between machines.
The catalog is deliberately small. Every model is tested offline on real laptops for answer quality (a grounded question-answering set in German and English, scored without a cloud judge), decode speed and peak RAM, and the app recommends one model for your hardware so you never have to compare quants yourself. Weights are verified by SHA-256 before use.
| Your RAM | Recommended chat model |
|---|---|
| 8 GB | Qwen3.5 4B (UD-Q4_K_XL) |
| 12 to 15 GB | Gemma 4 E2B Instruct QAT Q4_0 |
| 16 to 23 GB | Qwen3.5 9B (UD-Q4_K_XL) |
| 24 GB | Qwen3.8 27B UD-Q4_K_M |
| 32 GB and up | Qwen3.8 27B UD-Q5_K_M |
Supporting models: Multilingual E5 Small (embeddings), BGE Reranker v2 M3, Whisper Small, Qwen2.5-VL 3B (vision), TranslateGemma 12B (translation, opt-in).
The full list with sizes, minimum RAM and licenses is in the
verified model catalog
and in the README on GitHub.
The benchmark protocol and measured numbers are in
docs/model-benchmarks.md.
Questions and bug reports go to GitHub Issues.