llama3 at 8billion params is weak sauce for anything serious, it just isn't in the same galaxy as Sonnet 3.5 or GPT-4o. The smaller and faster models like Phi are even worse. Once you progress past asking trivial questions to a point where you need to trust the output a bit more, its not worth effort in time, money and/or sweat effort to run a local model to do it.

A novice isn't going to know what they need because they don't know what they don't know. Try asking a question to LLaMA 3 at 8 billion and the same question to LLaMA 3 at 70 billion. There is a night and day difference. Sonnet, Opus and GPT-4o run circles around LLaMA 3 70b. To run LLaMA at 70 billion you need serious horse power as well, likely thousands of dollars in hardware investment. I say it again... the calculus in time, money, and effort isn't favorable to running open models on your own hardware once you pass the novice stage.

I am not ungrateful that the LLaMA's are available for many different reasons, but there is no comparison between quality of output, time, money and effort. The API's are a bargain when you really break down what it takes to run a serious model.