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.
Intro to the Jev Model: Dropping Autoregression for Decision-Making
A brief introduction to the Jev model: it abandons the traditional autoregressive architecture and cannot directly output plain text, but it can make decisions, making it worth special attention.
Here's a simple introduction to the Jev model for everyone—this is absolutely a model that deserves special attention. In simple terms, this model abandons the traditional autoregressive architecture; it has no way to directly output plain text. But it can make decisions! For
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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.
