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交易的依据，但该指标下跌并不意味着 AI 需求或模型层利润正在走弱。\nSilicon Data 表示，其 LLM Token Index 衡量的是样本中 API 用户每百万 Token 实际支付的价格，即「使用量加权价格」，并非 Token 使用量或总支出。该指数从 5 月 28 日的 2.07 美元降至 9 月 21 日的 1 美元，下降 52%，但今年 1 月至 5 月高点期间曾上涨 67%，因此价格变化本身不能直接作为 AI 行业景气度指标。\n该机构指出，指数近期下跌主要反映更多任务被分配给廉价、快速的模型，同时 AI 实验室持续推出更多中端模型。由于 Token 并不能完全代表 AI 能力，该指标也无法单独区分模型替代与更高效的 Agent 路由。\n相比之下，GPU 算力租赁市场仍显示需求强劲。Silicon Data 数据显示，非超大规模云厂商 H200 租赁价格从 6 月平均 2.87 美元升至目前 3.29 美元，9 月 19 日一度达到 3.32 美元；B200 目前为 5.76 美元，较同期上涨 7%，年初至今上涨 31%；B300 自 4 月底推出以来上涨 44%。\nSilicon Data 认为，随着 Agent 大规模应用，未来绝大多数 Token 可能来自廉价、快速模型，因此 Token 价格可以持续下降，同时总 Token 使用量仍大幅增长。该机构表示，真正高价值的任务仍可能集中在前沿模型上，而 AI 全面普及意味着对算力的需求可能「更多，而不是更少」。",1790219160000,true,"Blockbeats",null,"Thu Sep 24 2026 03:06:00 GMT+0000 (Coordinated Universal Time)",{"id":23,"title":24,"content":25,"publishTime":26,"important":18,"sourceName":10,"language":20,"dateString":27},190872,"招商策略：AI芯片市场正在形成GPU与定制ASIC并行发展的格局","火星财经消息,招商策略称，本周海外大模型竞争再度明显升温：OpenAI于9月4日发布GPT-6 Astra，Anthropic于9月2日推出Claude Fable 5.1与Claude Mythos 5.1，谷歌在同日发布Gemini 3.8 Flash，三家头部厂商在极短时间内完成新一轮旗舰或主力模型更新。从三个模型的共性趋势看，实际生产效率成为衡量前沿模型价值的重要标准，科研能力是旗舰模型最关注的细分方向之一。与此同时，不同厂商的产品路线也进一步分化：OpenAI强化计算机操作能力，Anthropic继续深耕Agent，谷歌则依靠Flash系列强化性能、速度与成本之间的平衡。ASIC放量重塑算力格局。博通最新财报进一步确认，AI算力正在加速重构，定制芯片成为AI算力扩张的重要环节。FY2026 Q3公司营收创历史新高，并给出未来两个财年的AI半导体收入指引，定制ASIC进入规模化部署阶段，并逐步成为头部模型厂商和云厂商优化推理成本、能耗和系统效率的重要选择。随着谷歌、Anthropic、OpenAI、Meta等客户推进多代XPU项目，AI芯片市场正在形成GPU与定制ASIC并行发展的格局。(财联社)",1788874260000,"Tue Sep 08 2026 13:31:00 GMT+0000 (Coordinated Universal Time)",{"id":29,"title":30,"content":31,"publishTime":32,"important":9,"sourceName":10,"language":20,"dateString":33},219819,"DeepSeek披露单GPU每小时可创造38美元计费收入，AI推理盈利能力引发关注","动察 Beating AI 快讯，DeepSeek 近期开源推理框架 DeepInfer，并披露其集群每天可处理 155 万亿 Token。按照 DeepSeek API 谷时价格折算，平均每 GPU 小时对应约 38 美元的理论计费收入，若按全年不间断运行计算，年化计费收入超过 33 万美元。 DeepSeek 通过专家并行、推测解码、异步调度及 KV Cache 优化等技术提升推理效率，但上述数字属于理论计费收入，并不等于实际营收或利润。实际收益还取决于 GPU 利用率、付费请求比例、硬件与电力成本，以及服务延迟等因素。 AI 行业正面临需求增长与盈利压力并存的局面。一方面，中小企业 AI 应用及 Agent 部署需求持续升温；另一方面，模型训练、推理服务和基础设施投入仍在侵蚀部分企业利润。据报道，CoreWeave 第二季度营收同比增长约 112% 至 25.75 亿美元，但仍净亏损 6.26 亿美元。 分析认为，推理效率提升有望扩大 AI 服务的利润空间，但高效生产 Token 并不必然意味着商业盈利。随着模型调用量增长，企业仍需解决算力成本、服务定价和客户付费意愿之间的平衡问题。",1792818540000,"Sat Oct 24 2026 05:09:00 GMT+0000 (Coordinated Universal Time)",{"id":35,"title":36,"content":37,"publishTime":38,"important":18,"sourceName":39,"language":20,"dateString":40},218826,"芝商所计划与Silicon Data推出AI模型Token支出可交易指数产品","PANews 10月21日消息，据彭博社报道，芝商所集团（CME Group）拟于AI指数初创公司 Silicon Data 合作推出基于AI模型Token支出的可交易产品，相关产品将基于其大语言模型（LLM）Token指数，根据使用量对不同AI模型的Token价格进行加权。Silicon Data首席执行官Carmen Li表示，市场对GPU算力成本已有较充分的认知，但对AI经济中的消费层仍缺乏了解。 今年8月，双方曾宣布计划推出基于GPU租赁成本的期货产品。Silicon Data表示，新的Token指数产品计划于未来几个月推出，但仍需获得监管批准。",1792581840000,"PANews","Wed Oct 21 2026 11:24:00 GMT+0000 (Coordinated Universal Time)",{"id":42,"title":43,"content":44,"publishTime":45,"important":9,"sourceName":10,"language":20,"dateString":46},218769,"英伟达DSX软件测试：Lambda集群Token吞吐量提高24%","火星财经消息,英伟达披露，Lambda在搭载英伟达HGX B200系统的概念验证测试中使用DSX MaxLPS软件，在固定电力预算下，集群Token吞吐量提高24%，GPU容量提高19%。(财联社)",1792576980000,"Wed Oct 21 2026 10:03:00 GMT+0000 (Coordinated Universal Time)",{"id":48,"title":49,"content":50,"publishTime":51,"important":9,"sourceName":39,"language":20,"dateString":52},218150,"Inception发布扩散大模型Mercury 3，支持百万Token上下文","PANews 10月20日消息，据Inception官方公告，该公司发布扩散式大语言模型Mercury 3，支持100万Token上下文。官方称，其在英伟达GPU上的生成速度达每秒1068 Token，多项基准测试表现超过GPT-6 Luna和Claude Haiku 5.5。标准定价为每百万输入Token 0.20美元、输出Token 0.70美元，首发期间半价。模型已通过Inception API、OpenRouter、Baseten和Vercel开放，兼容OpenAI API。",1792458960000,"Tue Oct 20 2026 01:16:00 GMT+0000 (Coordinated Universal 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