Jeff is a small 0.8B decision model fine-tuned from Qwen and Gemma for fast zero-shot classification tasks, making calibrated probability judgments between user-defined options in ~22-28ms. Trained entirely on local hardware using synthetic data, it matches or exceeds larger models on classification benchmarks while acknowledging weaker reasoning performance on complex tasks.