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MoonEP is an open-sourced high-performance communication library from Moonshot AI…

2026-07-27 · 15:26 UTC ·@Kimi_Moonshot ·0 min read

Brief

MoonEP is an open-source communication library for distributed MoE training and inference that reduces expert-parallel communication overhead at scale. Released by Moonshot AI on GitHub (MoonshotAI/MoonEP), it promotes perfectly balanced expert parallelism using a Dynamic Redundant Experts design to improve efficiency in large MoE systems.

Why it matters

MoonEP is an open-sourced high-performance communication library from Moonshot AI for distributed mixture-of-experts (MoE) workloads, published on GitHub at github.com/MoonshotAI/MoonEP.

Key details

  • The library focuses on making expert-parallel communication more efficient at scale by reducing communication overhead and implements a 'Perfectly Balanced Expert Parallelism' approach via Dynamic Redundant Experts.
Source evidence

We've open-sourced MoonEP, our high-performance communication library for distributed MoE workloads.

Built to make expert-parallel communication more efficient at scale, MoonEP helps reduce communication overhead in large MoE training and inference systems.

Explore on GitHub:
github.com/MoonshotAI/MoonEP

Link

GitHub - MoonshotAI/MoonEP: MoonEP: A Perfectly Balanced Expert Parallelism Library via Dynamic...

MoonEP: A Perfectly Balanced Expert Parallelism Library via Dynamic Redundant Experts - MoonshotAI/MoonEP
github.com