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How large AI models are actually trained in pieces
A deep, hands-on guide to training Mixture-of-Experts models — the architecture behind 18 of the top 20 open AI models. Read it and you'll understand what it means when a model has '700 billion parameters but only 40 billion active'.
It's an interactive, browser-based guide to training Mixture-of-Experts (MoE) models — models built from small 'experts' that switch on in parts instead of all at once.
When it helps
Useful if you want to understand how large AI models really work, not just the headline numbers; skip it if you need a quick practical result or ready-made code for your project.
Pros
- Written by Hugging Face researchers who trained these models themselves
- Packed with interactive visualizations from real training runs
- Explains the 'active parameters' phrase used in most model releases
- Nothing to install — runs straight in your browser
Cons
- Takes a day or two to read in full
- Experiments can't be reproduced — they used costly GPU clusters
- A book for understanding, not a tool for your project
How to set it up — step by step
- 1Open the guide at the address from the install block — no signup or install needed.
- 2Skim the sections on the router, load balancing, and experts to grasp the structure.
- 3Send the agent the text from the block below to get the router explained simply.
- 4Compare the agent's answer with the guide's router section to check it got things right.
- 5Read the guide in several sittings — there's a lot of material, no need to finish at once.
Text for your agent
Copy this and send it to your agent — Claude Code, Codex, any of them:
Open this guide https://huggingface.co/spaces/huggingface/moe-blogpost and explain in plain terms how the router splits text between experts and why that is cheaper than running the whole model at once.
Nothing to install — it runs in the browser.
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