---
title: "Mixture of Agents (MoA)"
description: "Mixture of Agents (MoA) is an innovative framework in Artificial Intelligence that combines the capabilities of multiple Large Language Models (LLMs) to enhance performance in Natural Language Processing tasks. In this architecture, several LLMs, referred to as \"agents,\" are organized into layers. Each agent processes inputs and generates outputs, which are then utilized by agents in subsequent layers for further refinement. This collaborative approach leverages the unique strengths of individual models, resulting in more accurate and comprehensive responses."
canonical_url: "https://promptmetheus.com/resources/llm-knowledge-base/mixture-of-agents-moa"
---

> Index of every page on this site: [llms.txt](https://promptmetheus.com/llms.txt)

Mixture of Agents (MoA) is an innovative framework in [Artificial Intelligence](https://promptmetheus.com/resources/llm-knowledge-base/artificial-intelligence-ai) that combines the capabilities of multiple [Large Language Models (LLMs)](https://promptmetheus.com/resources/llm-knowledge-base/large-language-model-llm) to enhance performance in [Natural Language Processing](https://promptmetheus.com/resources/llm-knowledge-base/natural-language-processing-nlp) tasks. In this architecture, several LLMs, referred to as "[agents](https://promptmetheus.com/resources/llm-knowledge-base/ai-agent)," are organized into layers. Each agent processes inputs and generates outputs, which are then utilized by agents in subsequent layers for further refinement. This collaborative approach leverages the unique strengths of individual models, resulting in more accurate and comprehensive responses.

Notably, implementations like [Together MoA](https://www.together.ai/blog/together-moa) have demonstrated superior performance, achieving a 65.1% score on the [AlpacaEval 2.0](https://github.com/tatsu-lab/alpaca_eval) benchmark, surpassing GPT-4 Omni's 57.5%. The MoA methodology exemplifies the potential of collective intelligence in advancing the capabilities of LLMs.

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