If a consumer is willing to buy hardware with powerful enough GPU from you, and pay for your model, and set it up, and maintain it, they are likely to value whatever you are offering enough to actually pay a lot per call/inference if you are offering your solution over an API.

Deploying the model on cloud and setting up a scalable API pipeline is a pain for the first time, sure, but I'd say it's waaay less pain than procuring, offering, and maintaining the model on physical hardware. Plus there is IP issues as you mentioned.

It's probably easier for you to hire a cloud or ML architect to setup a proper cloud pipeline and API for your model than shipping physical hardware. You can give a dummy model to your temporary hire to setup the pipeline for you.

幸運を

And what makes you think that (i) every good paper would be published in a conference/journal, and (ii) every paper that is published in a good conference/journal is good. My experience says both of these are wrong.