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: How State and Typed Questions Work
Jev is not a chatbot, agent, or paragraph-generating model; it takes a state plus typed questions (Choice, Score, Noul) and returns an answer, probability distribution, and confidence.
> meet Jev > not a chatbot, not an agent, and not a model generating paragraphs > give it a state plus typed questions > Choice, Score, or Noul > it returns an answer, probability distribution, and confidence > a Choice selects one option from a predefined set > a Score maps the
· 10 likesOpen on X
More like this
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.
