$500 fine-tuned 9B AI model outperforms frontier models on catalog review task

A team at FermiSense demonstrated that a 9-billion-parameter open model fine-tuned using reinforcement learning for just $500 outperformed leading frontier AI models on a product catalog review task. The result suggests that narrowly specialised, low-cost models can effectively compete with large general-purpose models for specific business applications.