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: typed answers with probabilities
Jev's founder introduces a model returning typed answers with probabilities, warning that confidence is not correctness.
Jev founder Diogo Almeida introduced Jev as a model that returns typed answers with probabilities That last part is where an agent can become more useful, or considerably more dangerous A confident answer is not a correct answer. For Choice and Score, confidence tells you how
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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.
