I mean SubQ claims to reason as good as the frontier models, not better, but reasonably as good, and is 5x cheaper, so the future might not be all in on overpriced LLMs. Data science devs don't engineer for scalable performance, they engineer for the model's capabilities first and foremost.

SubQ was validated by at least one third party, not sure if we'll see more confirmation, but 5x cheaper costs is worth it. None of the frontier models care enough about cutting costs of their models, only being the best in benchmarks.

https://subq.ai/