The GPT 3.5 API is cheaper than Google Translate. And in our testing (over a year ago) was better for translation. So I assume in that case the energy use is less?
I've not heard any claim that they're making a loss, only that they're structured as a kinda-but-its-weird not-for-profit.
Given they tripped and fell over a money printing machine and then chose to lower their API prices, it would be pretty surprising (but not impossible) if their API prices are currently subsidised.
GPT4 on the web is at a loss, $20/mo doesn't cover it unless someone's a rare user. GPT4 through API is not at a loss, and I doubt GPT3.5 is at a loss either.
Given that you can buy a at least a couple hours worth of GPU compute at $20, it's hard to believe the average user spends that much time (specifically waiting for the response) on GPT-4 on the web every month... Not to mention that they probably have optimizations that batch together queries at the same time and make things more efficient at scale...
I doubt energy usage dictate the final price in such a way. You can't compare two widely different products from two company at completely different development stage to infer the energy usage of their product
Although, the paper argues that we can create artificial datasets using the LLMs which would improve the special-case translation models without having to pay for the inference and latency time of the large models.
