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: Fast Request Routing
Jev checks each request before it goes to a large model, dividing tasks to the right model in under a second at almost no cost.
Stop sending every request to your biggest model Opening a report doesn't need Claude, asking for the news doesn't need Claude Opus That’s where Jev steps onto the scene It checks each request first, in under a second, for almost nothing And divides the tasks exactly it
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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.
