Part 6/8:
The architecture of Llama 4 focuses on efficient model training, utilizing FP8 for pre-training across 200 languages and capitalizing on 32,000 GPUs for enhanced efficiency. The model’s capacity for advanced length generalization holds potential for even more expansive context requirements in the future.
Despite these impressive specifications, there are inherent challenges such as licensing limitations, which may restrict accessibility for larger enterprises. The requirement of attributing Llama in created materials could deter some developers from fully embracing the technology.