Yibo Cai optimized the core inference kernel in the ggml-org/llama.cpp repository, focusing on ARM64 architectures. He delivered a new GEMM kernel implementation using i8mm instructions for the q4_k_q8_k quantization scheme, targeting improved performance across a range of batch sizes while maintaining perplexity. His work involved low-level optimization and performance tuning in C, ensuring API compatibility and maintainability for future enhancements. By aligning the changes with ongoing project discussions, Yibo established a solid foundation for further vectorization. The depth of his contribution is reflected in the careful balance between speedup and model accuracy, addressing both efficiency and reliability.