Nemotron-4-340B-Instruct is a large language model (LLM) developed by NVIDIA, specifically optimized for English single-turn and multi-turn dialogue scenarios. This model supports a context length of 4096 tokens and has undergone additional alignment steps such as supervised fine-tuning (SFT), direct preference optimization (DPO), and reward-aligned preference optimization (RPO). Based on approximately 20K manually annotated data points, the model leveraged a data synthesis pipeline to generate over 98% of the data used for supervised fine-tuning and preference fine-tuning. This enables the model to exhibit strong performance in human-like conversational preferences, mathematical reasoning, coding, and instruction following, and it can also generate high-quality synthetic data for various use cases.