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.
Researcher on Jev decision models: dedicated classifiers are valuable
Dr. Sebastian Wallkötter says he is both excited and confused by decision models like Jev; he loves the idea of a dedicated model category for zero-shot, prompt-driven classifiers and finds such specialized models truly useful.
I'm both excited and confused by decision models like Jev. On the one hand I love the idea of having a dedicated model category for zero-shot, prompt-driven classifiers. They are really really useful and it makes total sense to have a specialized model for this instead of
· 0 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.
