Skip to content
Tuesday, 27 October 2026
Tenesys AI News
Subscribe

Ling-3.0-flash

Change history

  1. 27 Oct 2026
    Boosting Large-Scale MoE Model Throughput on NVIDIA Hardware
    ParameterBeforeNow
    MoE BackendFlashInfer MXFP4Humming
    LM Head PrecisionFP32Online FP8
    Speculative DecodingNoneMTP3 (NEXTN layer)

News

Models· Important· 🧪 Worth Testing

Boosting Large-Scale MoE Model Throughput on NVIDIA Hardware

NVIDIA has documented a threefold optimization approach to accelerate MoE inference, tested on the 124-billion-parameter Ling-3.0-flash model. By utilizing specialized Humming kernels, FP8 precision for the LM head, and Multi-Token Prediction, developers can achieve a 42.5% throughput increase and a 24.5% reduction in latency.

NVIDIA Developer
Ling-3.0-flash · TENESYS AI NEWS