Jev classifies 724 live ads from 37 brands in 40s for $0.09 in tokens
sibraan_ · reddit · 2026-09-24
A viral demo by Matthew Berman shows Jev, a structured text classification model, processing 724 live ads across 37 brands in 40 seconds — 8,700+ classifications for $0.09 in tokens. The upstream pipeline uses Gemini + embeddings to extract visual/text tokens, which Jev evaluates against predefined schemas in a single forward pass (216ms median latency). It's a clean primitive for offloading basic classification from frontier models, though its 32k context and no memory make it a router, not an agent.
Related event: Classification Model Jev Goes Viral for Fast, Cheap AI Judgments(2 posts)→
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