The Llama 4 series represents a major shift in open-source artificial intelligence, moving toward capabilities and Mixture-of-Experts (MoE) architectures.
: The models use a "mixture of experts," where only a subset of the total parameters (e.g., 17 billion active parameters in the Scout model) are activated for any given task. This significantly reduces computational costs and latency while maintaining high performance. Laskamp4
: Unlike previous versions that relied on "bolted-on" vision components, Llama 4 was trained from the start with text, images, and video frames. The Llama 4 series represents a major shift
: A defining feature is the 10 million token context window available in some variants, allowing the model to "read" over 7,500 pages of text or process 20+ hours of video in a single prompt. Key Models in the Series : Unlike previous versions that relied on "bolted-on"