Maybe not in theory but definitely in practice, as we’ve seen with GPT-5. These companies are lightning money on fire. If they reduce the cost, expect a proportional decrease in quality. All of the GPT-5 anecdotes confirm this. When the data and anecdotes disagree, the anecdotes are usually right, and the data is usually bullshit.
No dude, the latest versions of the models it routes to are markedly poorer in performance than their predecessors.
I’m observing a law that states: There appears to be a direct relationship between model performance and cost, such that whenever a company claims to have reduced inference costs, customers immediately notice a corresponding decline in model performance.