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.
TypeSafe AI's Jev: How a Decision-Native Model Works
Introduces TypeSafe AI's Jev model: instead of generating tokens to reach an answer, it assigns probabilities over predefined outcomes, offering a decision-native approach to building AI systems.
After a long i m watching him…. And the topic is cooll … Jev by TypeSafe AI is an interesting take on how we build AI systems. It’s a decision-native model — instead of generating tokens to arrive at an answer, Jev operates over predefined outcomes and assigns probabilities
· 5 likesOpen on X
More like this
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.
