How Kimi K3 Stabilizes Training for Highly Sparse MoEs
jbhuang0604 · x · 2026-08-18
Explores how Kimi K3 prevents training collapse in highly sparse MoE architectures.
Key Technique: Stable LatentMoE
- Normalization on the routed branch.
- SiTU-GLU inside each expert.
- Quantile Balancing on the router.
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