A new framework called Multi-Stage In-Flight Rejection (MSIFR) enhances the efficiency of synthetic data generation in large language models by terminating low-quality outputs early, reducing token waste significantly. This method can lower token consumption by up to 78.2% while maintaining or improving accuracy, making it a valuable advancement for LLM applications.