NVIDIA Shows 3 Ways to Speed Up MoE Inference on DGX Spark, Lifting Ling-3.0-flash Throughput 42.5%

NVIDIA's technical blog describes three stacked optimizations for running Ant Group inclusionAI's 124B-parameter Ling-3.0-flash (5.1B active) on a single DGX Spark at batch size one: Humming MXFP4 MoE kernels, an FP8 LM head, and built-in NEXTN speculative decoding. Across all 1,319 GSM8K questions, decode throughput rose 42.5% (37.81 to 53.89 tokens/s) and mean latency fell 24.5%, with accuracy essentially flat (96.89% to 96.82%). NVIDIA notes that combining the FP8 LM head with MTP requires a shared LM-head module, otherwise the framework silently falls back and throughput drops below the unoptimized baseline.