Controlling Reasoning Effort in LLMs

Sebastian Raschka discusses the evolution of reasoning-based LLMs, specifically focusing on the new GPT-5.6 model family. He explains how developers can implement multiple reasoning-effort modes to optimize model performance.
Sebastian Raschka, PhD Jul 18, 2026 243 11 19 Share It has been almost two years since OpenAI released o1, a model that popularized the idea of LLM-based reasoning models. DeepSeek-R1 followed about four months later, together with details of a reinforcement learning with verifiable rewards (RLVR) recipe to train such reasoning models.
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