Meta's Llama 4 is a beast (includes 10 million token context)

Meta recently released Llama 4, their new open-source large language model family. The video provides a breakdown of the different versions of Llama 4 and their features.

Llama 4 is available in three different sizes: Behemoth, Maverick, and Scout. Each version has varying capabilities and parameters.

Llama 4 Scout is a general-purpose model capable of understanding both text and images. It has 109 billion total parameters and offers improved efficiency with 17 billion active parameters.

Llama 4 utilizes a mixture of expert models to activate specific tasks efficiently. This approach improves performance while conserving resources, such as using 17 billion active parameters on a single Nvidia H100 GPU.

Llama 4 Maverick features 128 experts and manages to operate with 17 billion active parameters on a single GPU. It offers competitive performance compared to other models like GPT-3.1 and Gemini 2.0.

Llama 4 Behemoth is a powerful model with 2 trillion parameters and 16 experts. It outperforms competitors in benchmarks, showcasing impressive capabilities.

The video emphasizes the benefits of open-source models like Llama 4, providing developers with more control and flexibility. The pricing is competitive, making it accessible for app development.