Microsoft Takes Aim at Jev With a Fast, Cheap Decision Model
Techstrong.ai, Tuesday, October 13th, 2026
Microsoft-Decision-1 returns calibrated probabilities for routing, classification and verification, challenging TypeSafe AI's Jev.
Tom Smith reports that Microsoft released Microsoft-Decision-1 in Foundry and on OpenRouter, a decision-scoring model post-trained from Qwen3.5-9B.
It returns a calibrated probability for each of a fixed set of answers instead of free text, which suits yes/no, multiple-choice, ratings and rubric grading in agent workflows.
It costs $0.042 per million input tokens, matching TypeSafe AI's Jev, and Microsoft claims top accuracy across 36 benchmarks and 2.5 times the speed of the runner-up, noting that 100ms saved on each of 20 sequential decisions removes two seconds.
Smith advises testing calibration on your own labeled data and keeping humans in the loop for consequential calls.