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How do you serve a Mixture-of-Experts model efficiently, and what makes expert parallelism hard?

MoE saves compute but is awkward to serve: experts must be sharded, tokens routed across devices, and batches balanced. The signal is the all-to-all communication and the load-imbalance problem, not the training story.

Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.

MoE saves compute but is awkward to serve: experts must be sharded, tokens routed across devices, and batches balanced. The signal is the all-to-all communication and the load-imbalance problem, not the training story.

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