Applying Mixture of Experts in LLM Architectures – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2025-05-22T19:52:13Z http://www.open-lab.net/blog/feed/ Kyle Kranen <![CDATA[Applying Mixture of Experts in LLM Architectures]]> http://www.open-lab.net/blog/?p=79605 2024-06-06T14:53:24Z 2024-03-14T20:01:00Z Mixture of experts (MoE) large language model (LLM) architectures have recently emerged, both in proprietary LLMs such as GPT-4, as well as in community models...]]> Mixture of experts (MoE) large language model (LLM) architectures have recently emerged, both in proprietary LLMs such as GPT-4, as well as in community models...

Mixture of experts (MoE) large language model (LLM) architectures have recently emerged, both in proprietary LLMs such as GPT-4, as well as in community models with the open-source release of Mistral Mixtral 8x7B. The strong relative performance of the Mixtral model has raised much interest and numerous questions about MoE and its use in LLM architectures. So, what is MoE and why is it important?

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