System 1 (Jev) Models: Faster and Cheaper Proxy to Frontier Models — With a Working Router

Last Updated on October 6, 2026 by Editorial Team Author(s): Muhammad Soliman Originally published on Towards AI. Jev, Laya, Kev and Nimble in one place — plus a short, open proof of concept that puts one in front of a LiteLLM proxy and picks the model for every request. Ask your coding agent to rename a variable, and it will load a few hundred billion parameters to do it. Is it worth to pass everything to LLM as is and waste hundreds of thousands of tokens for simple questions/routing/decisions — The Most Expensive Question You Ask an AI Is “Yes or No” and System 1 model was built to save alot of respond faster. The article explains why “System 1” (decision models) can replace expensive full LLM calls for routing and other typed decisions, contrasting it with System 2 token-generating models. It introduces how these models work (typed questions answered in one forward pass, returning probabilities with no generated tokens), covers the new availability of four options (Jev, Laya, Kev, and Nimble), and discusses how to read benchmarks carefully—these models are meant as bases to specialize via small fine-tuning sets, keep option sets small, calibrate confidence, and match hardware …

≈