Seems a bit unfair (or maybe just ill-informed?) to lump this in with the confusing mess that is model naming at OpenAI.
The parameter count is more more useful and concrete information than anything OpenAI or their competitors have put into the name of their models.
The parameter count gives you a heuristic for estimating if you can run this model on your own hardware, and how capable you might expect it to be compared to the broader spectrum of smaller models.
It also allows you to easily distinguish between different sizes of model trained in the same way, but with more parameters. It’s likely there is a higher parameter count model in the works and this makes it easy to distinguish between the two.
The parameter count is more more useful and concrete information than anything OpenAI or their competitors have put into the name of their models.
The parameter count gives you a heuristic for estimating if you can run this model on your own hardware, and how capable you might expect it to be compared to the broader spectrum of smaller models.
It also allows you to easily distinguish between different sizes of model trained in the same way, but with more parameters. It’s likely there is a higher parameter count model in the works and this makes it easy to distinguish between the two.