That's interesting. Is there any kind of mapping to these respective models somewhere?

Yes, I included a 'Model Selection Cheat Sheet' in the README (scroll down a bit).

I map them by task type:

Tiny (<3B): Gemma 3 1B (could try 4B as well), Phi-4-mini (Good for classification). Small (8B-17B): Qwen 3 8B, Llama 4 Scout (Good for RAG/Extraction). Frontier: GPT-5, Llama 4 Maverick, GLM, Kimi

Is that what you meant?

at the sake of being obvious, do you have a tiny llm gating this decision and classifying and directing the task to its appropriate solution?

>Before you reach for a frontier model, ask yourself: does this actually need a trillion-parameter model?

>Most tasks don't. This repo helps you figure out which ones.

About a year ago I was testing Gemini 2.5 Pro and Gemini 2.5 Flash for agentic coding. I found they could both do the same task, but Gemini Pro was way slower and more expensive.

This blew my mind because I'd previously been obsessed with "best/smartest model", and suddenly realized what I actually wanted was "fastest/dumbest/cheapest model that can handle my task!"