Comment by lumost
1 day ago
There is a perceived opportunity cost from someone using a lower-tier model on their task. What if the better model did a "better" job? what if my trials and tribulations are due to model quality?
If you are used to talking to opus5.5 medium, going to GPT6.1 luna low will feel like a step down. Why would any employee take the (personal) risk?
The way around that is to take the choice away from the individual. We expose three model aliases instead of model names, each mapped to the cheapest model that clears a benchmark threshold, and the cheapest one is the default. Moving up a tier is an explicit step you take when the default actually falls short, not a bet you make up front. We re-check the mapping every few days, since prices and rankings move that fast, and nobody has to change their setup when a mapping changes.
This would all be true if perceptions matched reality for model performance and productivity.