英偉達發佈Nemotron-Labs-TwoTower離散擴散語言模型，解決大模型逐token生成速度慢的痛點，權重已在Huggingface開源。該模型複用現有骨幹網預訓練權重，無需從頭訓練，顯著降低成本。採用60B雙塔架構，兩座30B網絡並行協同，每塔激活3B參數並搭載128個可路由專家模塊，提升生成效率。
英偉達開源Nemotron-Labs-TwinTower擴散語言模型，通過“雙塔”架構突破自迴歸模型的串行解碼瓶頸。該模型將生成任務拆分爲兩個子網絡，其中一個保持凍結，以並行方式提升文本生成吞吐量，爲大規模合成任務提供高效新解法。
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