DeepSeek-V3 and the case for auxiliary-loss-free MoE benchmarks
DeepSeek-V3 is benchmark-relevant not just because it is large, but because it combines auxiliary-loss-free load balancing, multi-token prediction, and FP8 training at scale — and MLCommons is now using it as a pretraining benchmark with a 671B/37B MoE reference setup, making it a meaningful test of modern sparse-training infrastructure rather than just another model card.