The Imperceptible Upgrade
Put an 8K display next to a 16K display. At normal viewing distance you cannot tell them apart. The 16K costs significantly more. AI models are heading in the same direction.
Each new generation arrives with higher benchmarks, better scores on standardized tests, and a price increase to match. The latest model costs 20-30% more per session. Does the output feel 20-30% better?
For most people, no! And "most people" is the only metric that matters for a product.
There is a point where incremental model quality hits diminishing perceivable returns. The improvements are real in the technical sense, but the average user asking the average question gets back an answer that is functionally identical to what the previous model produced. The difference exists on paper only.
This pattern happens in every technology cycle like CPU clock speeds, camera megapixels, audio sample rates, etc. They all reach a point where the numbers keep climbing but the human experience plateaus.
Intelligence probably has the same ceiling. Some power users will notice. But if 99% of users cannot tell the difference in their day-to-day work, does it matter? You are optimizing for the 1% while charging the 100%.
However you could say that these gains compound, that today's imperceptible improvement becomes tomorrow's foundation for something transformative. Well, maybe, but let call this what it is: a bet. Asking customers to fund the bet with a 30% price hike is a hard sell when they cannot point to a single thing the new model does better for them.
The smarter play is not always the bigger model. Sometimes it is a smaller model deployed more efficiently, fine-tuned for the actual tasks people use it for, priced at a point where the value is obvious rather than theoretical. Not every problem needs the frontier model. Most problems need a good-enough model that is fast, cheap, and reliable.
The AI industry is addicted to "bigger is better.", but the display industry already learned this lesson. Nobody buys 16K monitors. They are too expensive at this point and the difference is imperceptible.
A practical note: at ChatBotKit we support multiple models across providers precisely because one size does not fit all. The best model for a task is often not the most expensive one - it is the one that delivers perceivable value at a sustainable cost. Our users choose the model that works best for them, not the one with the highest benchmark.