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.
TypeSafe AI's Jev: No Text Generation, Just Calibrated Decisions
Introducing TypeSafe AI's Jev model: it takes state and typed questions (Choice, Score, yes/no) and returns calibrated decisions in 70–500ms at $0.042/M input tokens, with every valid answer defined in advance.
The most interesting new AI model doesn't generate a single word of text. Jev by TypeSafe AI takes state + typed questions (Choice, Score, yes/no) and returns calibrated decisions in 70–500ms at $0.042/M input tokens. Every valid answer is defined in advance — so it can't
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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.
