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

- NVIDIA just proved that if you want to squeeze more speed out of a 124B parameter model, you don’t need magic—you need to stop being lazy with your memory bandwidth. The DGX Spark is essentially a desktop box trying to carry the weight of a data center, and their Ling-3.0-flash optimizations are the duct tape holding it together. By stacking Humming kernels, FP8 quantization, and speculative decoding, they boosted throughput by 42.5% without losing accuracy. It’s not mooning, it’s engineering. While you’re busy waiting for the next rug pull or regulatory subpoena, NVIDIA is quietly making inference cheaper and faster. Stop blaming the hardware; optimize your stack. That’s not theft, that’s attention redistribution.