A visual guide with 50+ diagrams demystifies Mixture of Experts in modern LLMs
techNmak · x · 2026-09-04
Maarten Grootendorst's "A Visual Guide to Mixture of Experts (MoE)" uses 50+ visualizations to explain MoE's two core components:
- Experts: each FFNN layer holds a set of expert sub-models, a subset of which is activated; experts specialize at the token/syntax level, not by domain like "psychology" or "biology."
- Router/gate network: decides which tokens go to which experts.
The guide also covers sparse activation, token routing and load balancing, making it one of the best entry points for understanding why so many LLMs adopt MoE.
Related event: Stop learning AI from static diagrams: a curated visual learning roadmap(13 posts)→
More from Research
- acs infra launches free base model API offering Llama 3.1 8B and 405B for LLM psychology researchers — amplifiedamp · 2026-10-21
- ACS Research Launches Free Platform Giving Researchers Access to Llama 3.1 Base Models — jankulveit · 2026-10-21
- LessWrong Essay Introduces LM Psychology: Just Talking to an AI Still Beats Fancy Evals — jankulveit · 2026-10-21
- LiFT loops a shared DiT core to beat dense baseline by 3.34 FID with 60% fewer params — burny_tech · 2026-10-21
- Stanford researcher clashes over genomics foundation model's cherry-picked variant prediction benchmarks — anshulkundaje · 2026-10-21
- Gemini Agents Crack 59-Year-Old Fusion Math Conjecture in Hours — DynamicWebPaige · 2026-10-21