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 Model: Evaluating States to Produce Structured Decisions
JEV evaluates states and outputs structured decisions instead of relying on sequential token generation, aiming to let AI decide without long text.
🤖 E se a IA não precisasse escrever um textão para tomar uma decisão? É justamente essa a proposta do JEV: em vez de trabalhar apenas com geração sequencial de tokens, ele foi pensado para avaliar estados e produzir decisões estruturadas. ⚡ Enquanto um LLM tradicional
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Pricing, evaluations, and the name Jev
The launch thread explains code-and-AI workflow evaluations, the input price announced at launch, and free output tokens.
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.
