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.
User tries Jev: rule-based bulk classification and scoring
A user shares first impressions of Jev, noting it doesn't just give a black-and-white verdict but a number for how dark something is, and mentions efficiency gains in rule-based bulk classification and tagging, with plans to explore more uses.
巷で話題のJevといふものをさわりはじめる。 なるほど、白黒はっきりつけてくれるというより、どれだけ黒いかを数字で教えてくれるAIなんだな。 何かをルールに添って大量に仕訳したりタグつけするのは捗るとかなんとか。もう少し触って色々活用出来そうなところ考えてみよう。
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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.
