Why: LLMs are increasingly becoming multimodal, so an image "token" or video "token" is not as simple as a text token. Also, it's difficult to compare across competitors because tokenization is different.

Eventually prices will just be in $/Mb of data processed. Just like bandwidth. I'm surprised this hasn't already happened.

Yes you can. The community creates quantized variants of these that can run on consumer GPUs. A 4-bit quantization of LLAMA 70b works pretty well on Macbook pros, the neural engine with unified CPU memory is quite solid for these. GPUs is a bit tougher because consumer GPU RAM is still kinda small.

You can also fine-tune them. There are lot of frameworks like unsloth that make this easier. https://github.com/unslothai/unsloth . Fine-tuning can be pretty tricky to get right, you need to be aware of things like learning rates, but there are good resources on the internet where a lot of hobbyists have gotten things working. You do not need a PhD in ML to accomplish this. You will, however, need data that you can represent textually.

Source: Director of Engineering for model serving at Databricks.