Skip to the document
Madhuopen lab
Outcome School · Transformers and architecture15 min read

by Amit Shekhar · 9 April 2026

Mixture of Experts Explained

The Mixture of Experts (MoE) architecture - understanding what experts are, how the router picks them, why MoE makes large models faster and cheaper, and why it powers many of today''s most powerful Large Language Models (LLMs).

2,918 words#llm#ai#machine-learning4 recall cards

Mixture of Experts Explained
Read on Outcome School ↗then come back to lock it in
Before you read, guess

How are the experts in a Mixture of Experts model structured and specialized?

Ten seconds, a guess, then read — a wrong guess still makes the answer stick.

What this article covers

  1. The Big Picture
  2. Why Was Mixture of Experts Needed?
  3. What Is an Expert?
  4. The Router
  5. Where Does MoE Sit Inside a Transformer?
  6. Sparse Activation
  7. Active Parameters vs Total Parameters
  8. Load Balancing
  9. How Outputs Are Combined
  10. Advantages of Mixture of Experts
  11. Challenges of Mixture of Experts
  12. Why MoE Powers Many Modern LLMs
  13. Summary

The article lives on outcomeschool.com. Read it there, then come back: the tutor in the margin has read it and will answer questions, and the questions below check what stayed.

Before you go

In one sentence, what was this chapter about?

From memory, without scrolling up. Writing it is what makes it yours; the grade is only to show you what you had.

How sure?