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Introducing System One Models and Jev

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Why This Matters

TypeSafe AI's launch of the Jev model signals a shift from chat-optimized LLMs toward specialized 'System One' models built for fast, structured decision-making rather than text generation. This matters because many real-world automation tasks need instant, reliable, machine-readable outputs rather than conversational responses, and Jev claims to deliver comparable intelligence at two orders of magnitude greater speed and efficiency while eliminating hallucination risk. If the claims hold up, this could unlock a new wave of software automation that pairs large language models with faster, more trustworthy decision engines.

Key Takeaways

Diogo Almeida, founder, TypeSafe

Models have been superhuman at chat for years, so where is all the automation?

This has been my driving question for the last four years. At OpenAI, I helped build the methods that made language models useful at following instructions and talking with people. That work ended up as the research behind ChatGPT. At the time, I thought maybe chat models would lead to AGI, but despite the hype it became obvious to me that there was something really big missing.

After two years in stealth, countless technical challenges, and research breakthroughs… I am beyond excited to announce that today, TypeSafe AI is releasing our first System One Model: a new class of frontier models built to make fast, structured decisions that software can use directly.

We built a new stack entirely focused on automation: with a new model architecture, parallel sampler for maximum efficiency, and training method we call Reinforcement Learning for Calibrated Decisions (RLCD).

Our first public model is Jev, available today in early access. Jev achieves similar levels of intelligence on System One tasks compared to existing LLMs, while being two orders of magnitude faster and more efficient. While Jev gives up string generation, it’s optimized for structured outputs and can’t hallucinate.

Think of Jev as a frontier-intelligence function call: unstructured state in, typed probabilistic decisions out.

Extraordinary claims require extraordinary evidence so see below for the receipts. 💅

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