Five local models, 6.8 GB of weights: my open-source Mac meeting notetaker
https://preview.redd.it/xs01ds930nsh1.png?width=4800&format=png&auto=…
Back in July I shared LokalBot here. It's a free, open-source Mac app that records your meetings and keeps a daily summary of your activity, all on-device.
0.9.2 came out today. Since July I've benchmarked every model in it and swapped most of the defaults for smaller ones. The whole stack is now 6.8 GB:
- Qwen3-ASR 1.7B (MLX, 8-bit): transcription
- Nemotron 3 (Core ML): who spoke when
- Qwen3.5 4B Q4\_K\_M (llama.cpp): notes and action items
- Harrier 0.6B Q8\_0: search embeddings
- LFM2.5 1.2B Q4\_K\_M: autocomplete in any app
- Apple Vision: screen OCR (opt-in)
A few numbers from my M4 Max (48 GB):
- 26-min meeting to finished notes in 33 s warm, \~85 tok/s decode
- Speaker error went from 43.4% to 14.6% DER on AMI. That's against my old pyannote setup, so it says more about my config than about pyannote.
- Autocomplete p95 went from 1.83 s (Gemma 4 E4B) to 0.49 s
There's also a read-only MCP server and CLI, off by default, so Claude Code or any other MCP client can pull context from your meetings.
I don't have any 16 GB or other M series numbers yet. If you've got one of those, especially M5 or M6 I'd love to see what you get.
I also tried MiniCPM5 2B for notes. It was smaller and faster, but it got stuck repeating itself on one summary and assigned action items to the wrong person. I kept Qwen3.5 4B as the default as saving a few seconds wasn’t worth getting who agreed to do what wrong.