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.
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.
The launch thread explains code-and-AI workflow evaluations, the input price announced at launch, and free output tokens.
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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.
Jev Model Achieves $42 per Billion Tokens via Parallel Computation
The post claims Jev uses non-transformer parallel computation at $42 per billion tokens, discusses potential impact on ChatGPT and Anthropic, and suggests a shift toward LLMs as interfaces with a harness backend.
