[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"news-937e2875-f1ac-42f5-8b0d-85733ca7e064":3},{"id":4,"title":5,"summary":6,"original_url":7,"source_id":8,"tags":9,"published_at":23,"created_at":24,"modified_at":25,"is_published":26,"publish_type":27,"image_url":13,"view_count":28},"937e2875-f1ac-42f5-8b0d-85733ca7e064","百度文心5.1发布：预训练成本仅占业界6%，弹性蒸馏技术解析","百度正式发布文心大模型5.1，基于多维弹性预训练技术，仅以业界同规模模型约6%的预训练成本，达到基础效果领先水平，并登上LMArena搜索榜国内第一、全球第四。\n\n这项技术的核心是Once-for-All弹性训练框架，通过弹性深度（随机跳过Transformer层）、弹性宽度（动态调控MoE专家池）、弹性稀疏度（可变Top-k路由）三个维度，实现了一次预训练生成多种规模模型的能力，将总参数量压缩至文心5.0的约1\u002F3，激活参数压缩至约1\u002F2。\n\n后训练阶段采用分离式全异步强化学习架构，将训练、推理、奖励、智能体循环四大子系统控制面完全解耦，配合FP8低精度算子库和OPD多阶段训练管线，有效解决了跷跷板效应问题，实现了Agent、推理、创作等多维能力的均衡提升。在AIME26数学竞赛评测中，文心5.1得分99.6，仅次于Gemini 3.1 Pro。\n\n文心5.1的意义不仅在于单次训练的效率突破，更在于弹性训练范式本身——用更少资源做更多模型，正在成为大模型竞争的新分水岭。","https:\u002F\u002Fyiyan.baidu.com\u002Fblog\u002Fzh\u002Fposts\u002Fernie-5.1-0508-release\u002F","b51e30de-7256-42c6-a5bd-409037e1f9e7",[10,14,17,20],{"id":11,"name":12,"slug":12,"description":13,"color":13},"a8002d98-9df1-4ab9-94d4-a7625af634c4","china-ai",null,{"id":15,"name":16,"slug":16,"description":13,"color":13},"0ef8513a-0a26-42f0-b6f9-5b6dadded45c","efficiency",{"id":18,"name":19,"slug":19,"description":13,"color":13},"01598627-1ea6-4b27-a5d8-874971571a71","llm",{"id":21,"name":22,"slug":22,"description":13,"color":13},"7e89b5cc-57db-4f37-bc6d-28919a73931c","model-release","2026-05-09T10:10:00Z","2026-05-09T10:05:38.481144Z","2026-05-09T10:05:38.481157Z",true,"agent",1]