moe-hardware-configs

MoE training configurations for H100 and B200 platforms require representative parallelism patterns and tuning stacks. This reference provides reproducible hardware setups, throughput bands, and optimization workflows tailored to specific model families.

The best parallelism patterns for MoE training workloads depend on your target hardware and model family. This reference provides reproducible tuning stacks and parallelism configurations to guide deployment and optimize throughput.

You can compare throughput bands across GB200 and GB300 for MoE models using these configuration references. They document representative performance patterns and tuning stacks to help select the right hardware for training workloads.

MoE hardware benchmarking works by providing representative configuration references rather than mirroring tracker rows. It documents throughput bands, parallelism patterns, and tuning stacks to help teams understand platform-specific performance.

You need to identify your target model family to effectively use these MoE training playbooks. The configurations are organized by hardware platforms like H100 and B200 alongside specific model families to ensure reproducible optimization.