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 founder explains how Jev works in 1-hour masterclass
The founder of Jev released a 1-hour masterclass breaking down how Jev actually works: LLMs → Decisions → Verification → Coding Agents, covering why LLMs alone aren't enough, the three primitives behind Jev, and turning huge AI tasks into tiny reliable steps.
The founder of Jev just dropped a 1-hour masterclass on how Jev actually works LLMs → Decisions → Verification → Coding Agents 0% → 0:40 - why LLMs alone aren't enough 25% → 20:27 - the 3 primitives behind Jev 50% → 26:15 - turning huge AI tasks into tiny reliable
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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.
