Mixture of Experts
Definition
Mixture of Experts combines multiple subnetworks; Sparse MoE selects only a subset per input.
A model architecture that combines outputs of multiple subnetworks or experts; in Sparse MoE, a router activates only a subset per input.
Simply explained
Like a specialist group from which some members are selected per task; their collaboration also incurs overhead.
Why it matters in practice
Helps realistically assess model quality, limits, and technical decisions.
Example from business
In a Sparse MoE, a router forwards tokens to a few selected experts.
Limits and pitfalls
- Equating parameter count with computational cost or ignoring routing imbalance and communication.
Origin & history
MoE dates back to the 1990s; sparse gating made very large models more practical.
Use in mid-sized companies
- Possible example: A development team tests a Sparse MoE model for a limited set of tasks. It measures routing distribution, communication, resource requirements, and quality on the target hardware.
Frequently asked questions
What does Mixture of Experts mean?
A model architecture that combines outputs of multiple subnetworks or experts; in Sparse MoE, a router activates only a subset per input.
Which mistakes should be avoided?
Equating parameter count with computational cost or ignoring routing imbalance and communication.
Sources
Source checked on 10.10.2026. Editorial use cases are hypothetical; no evidence of real customer results.
Editorially reviewed on: