<ul><li>LLaMA 4 represents a significant leap in AI architecture, combining Mixture-of-Experts (MoE) design with native multimodal integration (text + image), a record-breaking 10 million token context window, and major improvements in reasoning, coding, and comprehension.</li><li>LLaMA 4 outperforms larger models like LLaMA 3's 405B dense variant with less compute, thanks to its Mixture-of-Experts design that activates a subset of expert modules per input.</li><li>LLaMA 4 is natively multimodal, fusing text and image tokens at the input layer and processing them through a unified transformer backbone. It allows seamless vision-text reasoning and analysis.</li><li>LLaMA 4's architecture, training methodology, performance, configurations, use cases, limitations, and access details are covered in this article.</li></ul>

Meta Released LLaMA 4: Multimodal AI with 10M Context

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