The latest Flash-Decoding method developed by the FlashAttention team significantly enhances the inference speed of large Transformer architectures, especially beneficial for processing long-context LLM models. Benchmark tests have shown that Flash-Decoding accelerates long sequence decoding by 8 times and exhibits better scalability across various sequence lengths and batch sizes. This innovation is poised to play a crucial role in future natural language processing tasks. The usage of Flash-Decoding is also relatively straightforward, automatically selecting its application based on the size of the problem, thereby bringing significant performance improvements to the AI field.