The GPT-5.4 step-by-step reasoning dataset is a high-density synthetic reasoning dataset designed for long-chain reasoning (CoT) modeling and complex problem-solving tasks. The dataset is built on a "Master-Architect" workflow, using gemini 3 flash to generate challenging hints, and combining this with the GPT-5.4 Reasoning Core to complete multi-step reasoning and result generation. This dataset contains approximately 1,500 elite-level samples, covering highly complex fields such as mathematics, programming, and medicine. The task difficulty is uniformly set at the "Grandmaster" and "Beyond-PhD" levels. The data samples include complete multi-step reasoning processes and verified final solutions, making them suitable for scenarios involving long-chain logical derivation and assessment of extreme reasoning abilities.