Turning GLM-5.3-Flash into a Jev-like decision model

Researchers demonstrated how to convert GLM-5.3-Flash, a standard large language model, into a fast decision-making system comparable to specialized models like Jev by extracting typed decisions with confidence probabilities in a single forward pass. By crafting prompts to leverage the LLM's underlying probability distributions rather than generating full JSON responses, this approach achieves comparable accuracy and speed to dedicated decision models while additionally enabling decisions on images. This method addresses the cost and speed limitations that previously prevented LLMs from being practical for high-volume decision-making tasks.