NVIDIA details three inference optimizations for DGX Spark

NVIDIA said three software optimizations can materially improve inference on DGX Spark when running Inclusion AI’s Ling-3.0-flash model, with the biggest gains coming from speculative decoding once the components are configured to work together. In a post published Oct. 27, 2026, the company reported faster token generation and lower end-to-end latency, while also warning that one integration misstep can make the combined setup slower than the unoptimized baseline. The evaluation used Ling-3.0-flash-fp4, a mixture-of-experts model with 124 billion total parameters and 5.1 billion active parameters per token, according to NVIDIA’s post.

Source: Blockchain.News