But if you just want to play around rather than code, you really might find the Gemma 4 12B model worth mucking about with just so you've gone through the steps. Especially if you want to muck about with image analysis or audio transcription.

If you're writing PHP I think you could even find it good enough. I've been modestly surprised. You can do that basic fiddling with the Edge AI Gallery app, which can enable thinking and has a customisable system prompt and some agent support.

You could also try the 14B Deepseek R1.

Honestly even if it is not good enough, if you are anything like me, I think you'll find that going through this process is really quite educational — it has made a lot of things more concrete for me in a way that I have found reassuring and valuable.

omlx + gemma 12b 6 bit + pi

it’s feasible for sure

MoEs for speed (qwen 35b, cohere 30b, gemma 26b)

Dense for more methodical work (qwen 27b [reigning champ], gemma 31b, gemma 12b)

MoE i recommend 5bit+

Dense i think 4 bit is okay

Play with your context size, you don’t really need that much, have lazy loading for tools and mcps

my pi extensions for anyone looking for a skinny quick setup, i have use `--no-skills` right now too:

    "npm:pi-codex-goal",
    "npm:pi-simplify",
    "npm:pi-mcp-adapter",
    "git:github.com/elpapi42/pi-minimal-subagent",
    "npm:@wierdbytes/pi-statusline",
    "npm:@aliou/pi-guardrails",
    "npm:pi-lens",
    "npm:@juicesharp/rpiv-todo",
    "npm:pi-hashline-readmap",
    "npm:@mrclrchtr/supi-review",
    "npm:pi-cmux",
    "npm:@mrclrchtr/supi-context",
    "npm:pi-tool-search"

Also there are smaller, still usefull models that can run on 8GB or less.