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.
Explaining the Thesis on Using Jev for Coding Agents
The post explains Diogo's thesis on using Jev for coding agents, with examples on context management and KV caching.
Here’s an explanation of Diogo’s thesis on using Jev for coding agents, broken down with some examples 1) Context Management & KV Caching
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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.
