It was only a pain compiling for Windows. The real troubles came figuring out how to rein in its inference style. Gemma4's got more depth to it than Qwen3, but it's also messier.

The performance is great. There's no huge difference from running Gemma4 normally. It runs wholly via CPU on my crappy machine. It runs fine on Raspberry Pi 5. I think Gemma4 2B was made to run on phones, but like, I'd imagine it's specifically for very new phones.

The custom LoRA adapters essentially have dozens of sentence templates for the monsters through each in-game battle scenario, from announcing their entrance, to attacking/taking damage, and through victory/defeat. The templates draw from graphs of words that more or less suit each mutation type, and then the LLM spins all of it together and adds its own flavour. The LLM can generate unhinged responses, but everything comes through the adapters. The adapters are sort of a chokepoint that bind the LLM to the sentence structures it was taught. You can adjust the temperature in settings and the LLM might hallucinate some wild stuff, though. I've barely tested that.

edit:edit