Recent advancements in generative AI algorithms have introduced models like Transformer, Mamba, xLSTM, and Jamba.

Jamba is a hybrid model combining Transformer and Mamba layers with a mixture-of-experts architecture, offering flexibility and high performance.

BitNet, a 1-bit Transformer model, showcases competitive performance in language modeling while reducing memory usage and energy consumption.

The quantized version of BitNet b1.58-3B model on Hugging Face repository further demonstrates its efficiency in resource usage.

These developments present a promising solution for large language models, balancing performance and resource efficiency for researchers and developers in natural language processing.