NewsTechnical

This AI Model Does’t Use Words?!

Matt Wolfe

Typesafe AI released Jev, a new AI model that outputs structured decisions (choices, scores, or booleans) instead of generated text like traditional LLMs. This approach makes Jev dramatically cheaper and faster, with input costs at 4 cents per million tokens and free output tokens.

Summary

A new AI model called Jev from Typesafe AI is generating significant interest due to its fundamentally different approach compared to models like GPT. While traditional language models generate new text and code to make decisions, Jev skips the text generation step entirely and outputs structured values directly. The model supports three types of structured outputs: choices, scores, and binary values (true/false). This architectural difference provides substantial practical advantages. The cost efficiency is remarkable—input tokens cost only 4 cents per million tokens (or $42 per billion tokens), while output tokens are free because they are too inexpensive to meter separately. Beyond cost, Jev offers significant speed advantages over traditional LLMs since it doesn't need to generate lengthy text outputs. To demonstrate the model's capabilities, Steven Tay created an application that uses Jev to detect whether URLs are malicious before users visit them. The implementation is straightforward; developers can use coding assistants like Codeex or Claude Code to specify what they want Jev to do, and these tools can generate the necessary code to run Jev.

Key Insights

  • Jev differs from GPT-style models by skipping text generation entirely and outputting structured values directly for decision-making
  • Jev supports three types of structured outputs: choices, scores, and boolean values (true/false)
  • Jev's input tokens cost 4 cents per million tokens while output tokens are completely free because they are too cheap to meter
  • Steven Tay demonstrated Jev's practical capability by building an app that detects malicious URLs before users visit them
  • Developers can easily create Jev applications by using coding assistants like Codeex or Claude Code to generate the implementation code

Topics

Jev AI model by Typesafe AIStructured outputs vs text generationCost efficiency of JevSpeed advantagesPractical application - malicious URL detection

Transcript

[0:00] But there was something else causing a lot of buzz this week. And that's a model out of a company called Typesafe AI called Jev. When you think of like the GPT models, those create new text. Even when you ask it to make decisions for you, it's still creating text and writing code that then goes and makes those decisions. Jev, on the other hand, just skips straight to the decisionmaking. The output from existing LLM are, you know, strings and generated text. The outputs from Jev are structured values. And there's really [0:30] three types of structured outputs. You can give it a choice, a score, or a new, which is basically, you know, true or false.…

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