Nemotron-SFT-Math-v4 is a mathematical inference dataset released by NVIDIA in May 2026. The related research papers are as follows: Nemotron-Math: Efficient Long-Context Distillation of Mathematical Reasoning from Multi-Mode SupervisionIt aims to solve the problems of inconsistent quality of traditional mathematical datasets, non-standard reasoning trajectories, low accuracy, and limited scenarios. It effectively improves the model's structured reasoning, multi-trajectory reasoning, and answer verification capabilities. It is widely used for fine-tuning of large-scale mathematical reasoning models, reasoning trajectory analysis, answer verification algorithm development, long-context reasoning system construction, and model reasoning robustness evaluation. This dataset contains 545,431 training samples, including 285,516 COT reasoning samples and 259,915 TIR tool reasoning samples. It covers mathematical scenarios in competitions and university research in algebra, geometry, number theory, combinatorics, etc. The data is annotated using a hybrid manual and automated method and includes standardized fields such as unique number, question text, multi-turn dialogue, standard answer, source, and protocol.