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.
Discussion on JEV models' sensitivity to choice order
AVB points out that JEV-like models change answers depending on the order of choices, calling it a major flaw, and plans to repurpose Qwen3-0.6B into a decision model in a new video.
I have been looking at the Qwen3-0.6B architecture coz that's the model I will repurpose into a decision model in the new "JEV from scratch" video. Almost all JEV-like models change their answers depending on the order of the choices you sent it. IMO this is a major flaw, coz
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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.
