pancomplex

Not yet, but that sounds like a useful overview to add to the landing page!

It will automatically pick the best one for your HW on install

Sorry about that. I’ll make sure it cleans up after itself in the next update. What was the main issue you ran into?

I went back and forth with my coworkers on the naming and we essentially voted on Hob vs Garth. Vote came to Hob. Do you prefer Garth?

So basically allow you to point the LLM to a hosted model on your local network if I understand correctly?

thank you! Haha I always make it a point these days do handwrite these things. I think everyone is tired of overly verbose perfectly written AI text.

Thank you. Yes please fork that's exactly why I put it out on MIT license :)

Here's roughly what it picks today from my testing:

- 8 GB Mac (M1/M2): Gemma 4 E2B

- 16 to 18 GB Mac: Gemma 4 E4B

- 24 to 64 GB Mac: Gemma 4 26B A4B

- 128 GB Mac Studio: gpt-oss 120B

- Windows/Linux with an RTX 3060 or 4070 (12 GB) and 32 GB RAM: Gemma 4 26B, split between the GPU and system memory

- RTX 4090: Gemma 4 26B fully on the GPU

- No GPU, 16 GB RAM: a compressed Gemma 4 E4B on the CPU

High level, it looks at your memory and memory bandwidth and then picks the smartest one that stays above about 15 tokens a second with room for a decent context.

It's still pretty tricky to do this as a solo dev to keep feature parity in my experience (fun fact, even Claude's own Desktop app is made in Electron).

That being said, majority of the heavy LLM lifting happens natively with llama.cpp :)

Good call. Are you on PC/Mac/Linux?

Thank you! Would love to hear which ones you've used. Working with local files without anything going to the cloud was the main thing I wanted. I tried Jan, OpenWork, Chatbox and Lobe, and couldn't get that working well in any of them. If there's one I missed it would be great to check it out!!

Thank you! It finished the full game!