英伟达发布旗舰模型Nemotron 3：专为“智能体时代”设计

\u003cdiv class=\"rich_media_content\"\u003e\u003c!--NO_AD_ERROR_2--\u003e\u003cp style=\"text-align: center\"\u003e\u003c!--IMG_0--\u003e\u003c/p\u003e\u003cp\u003e12月15日消息，英伟达发布了新一代旗舰开源模型系列Nemotron 3，旨在为正在兴起的“智能体时代”提供核心动力。\u003c!--NO_AD_0--\u003e\u003c!--EOP_0--\u003e\u003c/p\u003e\u003c!--PARAGRAPH_0--\u003e\u003cp\u003e这个系列最大特点在于其采用的混合Mamba-Transformer专家模型架构，\u003c!--SECURE_LINK_BEGIN_0--\u003e英伟达\u003c!--SECURE_LINK_END_0--\u003e称该设计能够赋予AI智能体更高的准确性和任务可靠性。\u003c!--NO_AD_1--\u003e\u003c!--EOP_1--\u003e\u003c/p\u003e\u003c!--PARAGRAPH_1--\u003e\u003cp\u003eNemotron 3系列将按照参数规模分三个阶段发布，以满足不同复杂度的应用需求：\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eNemotron 3 Nano：\u003c/strong\u003e拥有300亿参数，专注于目标明确的高效任务，是该系列的效率先锋，目前已可用。\u003c!--NO_AD_2--\u003e\u003c!--EOP_2--\u003e\u003c/p\u003e\u003c!--PARAGRAPH_2--\u003e\u003cp\u003e\u003cstrong\u003eNemotron 3 Super：\u003c/strong\u003e参数规模达1000亿，专为多智能体协同应用设计，强调高精度推理能力。\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eNemotron 3 Ultra：\u003c/strong\u003e作为顶级型号，具备庞大的推理引擎和约5000亿参数，面向最复杂的应用场景。\u003c/p\u003e\u003cp\u003e在新的智能体AI时代，由多个协同工作的智能体（如检索器、规划器、工具执行器、验证器等）组成的系统，需要在海量上下文和长时间跨度中运行。\u003c!--NO_AD_3--\u003e\u003c!--EOP_3--\u003e\u003c/p\u003e\u003c!--PARAGRAPH_3--\u003e\u003cp\u003e这要求底层模型必须具备高吞吐量、强推理精度和长期一致性。为应对这一挑战，英伟达推出了全新的Nemotron 3开源模型系列，旨在构建高性能的专用智能体AI系统。\u003c!--NO_AD_4--\u003e\u003c!--EOP_4--\u003e\u003c/p\u003e\u003c!--PARAGRAPH_4--\u003e\u003cdiv powered-by=\"qqnews_ex-editor\"\u003e\u003c/div\u003e\u003cstyle\u003e.rich_media_content{--news-tabel-th-night-color: #444444;--news-font-day-color: #333;--news-font-night-color: #d9d9d9;--news-bottom-distance: 22px}.rich_media_content p:not([data-exeditor-arbitrary-box=image-box]){letter-spacing:.5px;line-height:30px;margin-bottom:var(--news-bottom-distance);word-wrap:break-word}.rich_media_content .qn-editor-copy p:not([data-exeditor-arbitrary-box=image-box]){letter-spacing:unset;line-height:unset;margin-bottom:unset;word-wrap:unset}.rich_media_content{color:var(--news-font-day-color);font-size:18px}@media(prefers-color-scheme:dark){body:not([data-weui-theme=light]):not([dark-mode-disable=true]) .rich_media_content p:not([data-exeditor-arbitrary-box=image-box]){letter-spacing:.5px;line-height:30px;margin-bottom:var(--news-bottom-distance);word-wrap:break-word}body:not([data-weui-theme=light]):not([dark-mode-disable=true]) .rich_media_content .qn-editor-copy p:not([data-exeditor-arbitrary-box=image-box]):not(.qn-editor-copy){letter-spacing:unset;line-height:unset;margin-bottom:unset;word-wrap:unset}body:not([data-weui-theme=light]):not([dark-mode-disable=true]) .rich_media_content{color:var(--news-font-night-color)}}.data_color_scheme_dark .rich_media_content p:not([data-exeditor-arbitrary-box=image-box]){letter-spacing:.5px;line-height:30px;margin-bottom:var(--news-bottom-distance);word-wrap:break-word}.data_color_scheme_dark .rich_media_content .qn-editor-copy p:not([data-exeditor-arbitrary-box=image-box]){letter-spacing:unset;line-height:unset;margin-bottom:unset;word-wrap:unset}.data_color_scheme_dark .rich_media_content{color:var(--news-font-night-color)}.data_color_scheme_dark .rich_media_content{font-size:18px}.rich_media_content p[data-exeditor-arbitrary-box=image-box]{margin-bottom:11px}.rich_media_content\u003ediv:not(.qnt-video),.rich_media_content\u003esection{margin-bottom:var(--news-bottom-distance)}.rich_media_content hr{margin-bottom:var(--news-bottom-distance)}.rich_media_content .link_list{margin:0;margin-top:20px;min-height:0!important}.rich_media_content blockquote{background:#f9f9f9;border-left:6px solid #ccc;margin:1.5em 10px;padding:.5em 10px}.rich_media_content blockquote p{margin-bottom:0!important}.data_color_scheme_dark .rich_media_content blockquote{background:#323232}@media(prefers-color-scheme:dark){body:not([data-weui-theme=light]):not([dark-mode-disable=true]) .rich_media_content blockquote{background:#323232}}.rich_media_content ol[data-ex-list]{--ol-start: 1;--ol-list-style-type: decimal;list-style-type:none;counter-reset:olCounter calc(var(--ol-start,1) - 1);position:relative}.rich_media_content ol[data-ex-list]\u003eli\u003e:first-child::before{content:counter(olCounter,var(--ol-list-style-type)) '. 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