Jev versus text-generating models
Jev does not generate free-form text. A side-by-side video compares parallel decision-making with token-by-token text generation.
Jev in the decision hierarchy: small bounded classification and routing
The author shares a decision hierarchy: deterministic problems get code, small bounded classification, routing, scoring, or fuzzy decisions use Jev, and generation, task completion, or moderate reasoning use a cheap API model.
My current hierarchy is becoming: Deterministic problem? -> Write code. Small, bounded classification, routing, scoring, or fuzzy decision? -> Use something like Jev. Generation, task completion, or moderate reasoning? -> Use a cheap API model like Luna or DeepSeek Flash.
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Pricing, evaluations, and the name Jev
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Jev Model: Decision-Making Probability Generation, 200× Faster and 400× Cheaper Than LLMs
This model is built for decision-making rather than text generation, outputting probabilities for each option in parallel instead of token-by-token responses. The author shares a simplified comparison of normal LLMs versus this Jev model.
