778: Mixtral 8x22B: SOTA Open-Source LLM Capabilities at a Fraction of the Compute — with Jon Krohn

Model Intro

The Mixtral 8x22B model, developed by the French startup Mistral, represents a significant advancement in open-source large language models. Jon Krohn explains that the model's name reflects its mixture of experts architecture, which includes 822 billion parameter expert sub-models. This innovative design allows the model to outperform other open-source models, including Meta's Llama, across various benchmarks and languages, while also being more cost-effective to run 1.

The Mixtral 8x22B is released under the Apache 2.0 license, allowing unrestricted use worldwide.

--- Jon Krohn

This permissive licensing, combined with its superior performance, positions Mixtral 8x22B as a groundbreaking tool for developers and data scientists 2.

   

Architecture

The architectural design of Mixtral 8x22B is centered around its mixture of experts approach, which is a key factor in its efficiency and performance. Jon Krohn describes how this model uses only a fraction of its total parameters during inference, significantly reducing computational costs and time 1. This design allows specific sub-models to handle specialized tasks, such as math or code generation, without engaging the entire model.

By using only 39 billion of its 141 billion parameters, Mixtral 8x22B saves about 75% of the cost and time compared to using the full model.

--- Jon Krohn

This efficiency makes it a powerful tool for real-world applications, offering state-of-the-art performance without the high resource demands of traditional models.