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 compaction has significant problems
The author points out many problems with Jev compaction, noting that on a public compaction eval it produced a programmatic rule that requires no Jev or other model.
Okay, everyone wants us to give the unbiased facts. Jev compaction here has a lot of problems. The biggest problems: - When I ran it on our public compaction eval (that you can run too), it resulted in a programmatic rule, that you dont need any Jev or other model for - 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.
