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Independent developer releases open-source 'Jevlike' model mimicking TypeSafe's Jev

A developer built an open-source model that mimics TypeSafe's proprietary Jev system, which scores a variable list of text options in a single pass rather than generating answers word-by-word. The project, released without official documentation from TypeSafe, includes working demos where the same attention-based scoring head selects Doom combat moves and chess moves from image inputs, along with checkpoints, code and a rendering pipeline to visualize decision traces.

TypeSafe AI launches Jev, a decision-focused model claiming 40-400x lower cost than LLMs

TypeSafe AI, founded by former OpenAI researcher Diogo Almeida, has released Jev in early access, a new type of AI model designed to make fast structured decisions rather than generate text. The company says Jev matches existing large language models on decision-making tasks while running 20-200 times faster and 40-400 times cheaper, using a new architecture and a training method called Reinforcement Learning for Calibrated Decisions.