Controlling Reasoning Effort in LLMs

# Summary OpenAI's recently released GPT-5.6 model family features multiple reasoning-effort settings, marking reasoning models as a standard component of modern LLM releases following the earlier popularization of such models by o1 and DeepSeek-R1. Reasoning models generate intermediate step-by-step reasoning traces rather than direct answers, and can be improved through both training scaling and inference scaling approaches. The article introduces methodology for developing reasoning models with multiple effort modes to control computational intensity during problem-solving.