Introducing Lev
Summary
Lev is a local decision engine that combines a fast encoder-based classifier with an escalation to a thinking LLM to enable offline, low-latency classification. The article contrasts Lev with Jev, discusses performance benchmarks, calibration techniques, and a gating mechanism that routes uncertain cases to heavier models, and explains how to run Lev as a standalone binary.