# Mixture-of-Agents

> Mixture-of-Agents (MoA) arranges language models in layers, where each model receives all outputs from the previous layer as auxiliary input and an aggregator synthesizes a final response.

- Identifier: PTL-0052
- Category: Self-Critique & Verification
- Canonical URL: https://protologue.com/t/mixture-of-agents/
- Also known as: MoA
- Introduced: 2024

## Description

Wang et al. reported that a mixture of open models outperformed a single strong proprietary model on an instruction-following benchmark.

## Related terms

- [Multi-Agent Debate](https://protologue.com/t/multi-agent-debate/)
- [Parallelization](https://protologue.com/t/parallelization/)

## Sources

- Wang et al. (2024). Mixture-of-Agents Enhances Large Language Model Capabilities. https://arxiv.org/abs/2406.04692

## Cite this entry

Protologue. (2026). Mixture-of-Agents. In Protologue: A Taxonomy of Prompting and LLM Techniques (v1.0.0, PTL-0052). https://protologue.com/t/mixture-of-agents/

License: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/)