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Introducing Jev: The System One Model

Diogo Almeida announces Jev after 2 years in stealth. 20-200x faster, 40-400x cheaper with output tokens free.

Open X (@CompleteSkeptic) ⚡ 20-200x faster · Free output tokens
Diogo Almeida

Diogo Almeida

@CompleteSkeptic

After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x cheaper (w/ output tokens free) • Frontier composable intelligence optimized for decisions AFAICT the shortest path to AI-based economic revolution

01 / The Decision

Non-autoregressive calibrated decisions for software workflows.

Jev sits between the incoming context and the next system action. Rather than generating lengthy, slow natural language that requires brittle regex parsing, Jev returns non-autoregressive, calibrated probabilities that downstream code can immediately execute.

02 / Typed Outputs
01choicePrimary action
02scoreConfidence score
03probabilityFallback route

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