Jev is pitched as a model for decisions, not text generation
A post describes Jev as taking program state and questions, then returning a typed answer with a probability—an alternative to using text-generating LLMs for routine agent decisions.
TLDR
A post argues that AI agents overpay for text generation when they only need routing, classification or relevance scoring. It presents Jev as a model built for those decisions rather than chat or code generation, claiming it is 193 times faster and 444 times cheaper.
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