Decision AI Models Explained: TypeSafe Jev vs Fastino GLiDE, GLiNER2.5-Decide and Open-Source Competitors

A new kind of AI model is trying to replace a very specific kind of LLM call: the one where you don’t want prose, you want a decision. TypeSafe AI’s Jev made the category hard to ignore, and within weeks Fastino Labs answered with GLiDE and GLiNER2.5-Decide while open-source copies popped up too. The pitch is simple. Send in text, ask a typed question, get back a choice, a score, or a probability that code can branch on directly.

Jev is built around three primitives: Choice, Score and Noul. Choice picks from a list with probabilities and confidence, Score grades against ordered levels, and Noul returns a 0-to-1 probability that a statement is true. TypeSafe says questions run in parallel against the same state, which keeps response time from growing much as you add more of them. It also says the model never generates strings, so it can’t produce a type error. Under the hood, TypeSafe points to a parallel sampler and a training method called Reinforcement Learning for Calibrated Decisions, or RLCD.

The practical draw is cost and speed. Jev is priced at $0.042 per million input tokens, with output free, and OpenRouter lists a 32K context window. TypeSafe reports end-to-end responses in 70 to 500 milliseconds. In its workflow evals across security incidents, trace observability, invoice processing and customer service, Jev hit 67.8% mean accuracy at $0.0004 per case and 0.4 seconds. That matched Claude Sonnet 5 on the same workflow, while the best comparison model reached 74.1% but cost more and took longer. Jev still trailed the top frontier setup by 6.3 points, and its scores were uneven across tasks, from 76.0% on customer service to 61.8% on invoice processing.

And that unevenness is part of the story. Decision models are not meant to replace writing or reasoning-heavy LLM work. They’re for bounded outputs: routing, triage, guardrails, reranking, evals, escalation decisions. TypeSafe, Fastino and the open-source crowd are all aiming at the same narrow slice of the stack, where a fast calibrated answer is more useful than a paragraph.

The market moved quickly enough that the comparisons already look crowded. Fastino’s GLiDE is a hosted API, while GLiNER2.5-Decide is open weights under Apache 2.0 and can run locally on CPU or GPU. Other open options include Laya, JevK5, OpenJev and kev. The larger point is not that one model has won. It’s that AI plumbing is starting to split into separate tools for writing and for deciding, and the boring one may end up paying the bills.