Using Jev as a router cuts cost to 1/13 of a flagship model
The author uses Jev as a front-end router to decide whether a task needs a large model; on 60 hard problems the setup matched a flagship model's accuracy at about 1/13 of the cost.
Jev is really f*ckin cheap it is not a chatbot. it does not write text. that is the whole new model. you give it a situation and a question, and it just picks an answer - yes/no, one option from a list, or a score - and tells you how confident it is. because it never writes anything back, you only pay for what goes in. ~$0.04 per million tokens in, output is free. a normal model bills you for every word it generates. here is the move from the article: stop making the expensive model answer everything. put Jev in front as a router. for each task Jev decides one thing - "does this actually need the big model?" easy ones go to the cheap model, only the hard ones get escalated to the flagship. on 60 hard math problems that combo scored the same as the $20 flagship - at about 1/13 of the price. the always-cheap model on its own lost 32 points. frontier accuracy, discount bill. that is it.