The "wall" is in increasing intelligence per cost. No one is saying the absolute intelligence won't continue increasing, it's that the rate of intelligence increase per cost is falling from super-linear growth rates to linear at the same time the companies are backing out the investor-funded subsidies they were using to buy adoption and user growth numbers. You're correct that there is a 'trickle down' effect to lower tier models but OAI/Ant are clearly using this to segment customers by willingness to pay and their IPOs depend on extracting the maximum amount possible from each segment.
That's why the prices of frontier models have been skyrocketing, though they are using every trick imaginable to mask this being clear and obvious. They take with price increases, token deflation, shifting plan levels and limits but muddy things more by giving back some (but always eventually less) with resets, subs, etc.
They absolutely have said that.
> That's why the prices of frontier models have been skyrocketing,
They haven't.
"The cost of achieving a given level of AI performance has fallen about 47% per quarter since 2023, or 13× per year."
"The cost of a given level of performance often falls fastest right after that level is first achieved, that is, when it is state of the art (SOTA). We see this pattern on three of our five main benchmarks of AI capability. Averaging across all five, cost falls 66% per quarter (75× per year) for performance that has just debuted as SOTA."
https://epoch.ai/publications/the-plunging-price-of-thought#...
On a per-token basis Fable 5.2 is cheaper than 5.1:
5.2: $8 per million input tokens and $40 per million output tokens.
5.1: $10 per million input tokens and $50 per million output tokens.
Compared to older (and much less capable) frontier models it is also cheaper. For example GPT-4 was $30 per million input tokens and $60 per million output tokens
https://developers.openai.com/api/docs/models/gpt-4
Be very careful comparing the Artificial Analysis "cost per task" scores. Fable 5.2 is expensive there because it is doing tasks the other models fail at.
Having these highly rated models reflects (potentially) the frontier of what they are capable of producing. Essentially its and advertisement and shows directionally where the smaller faster model's capabilities are headed.