[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"news-b0183d10-bcfd-44ed-a178-a2c813f10b69":3},{"id":4,"title":5,"summary":6,"content":7,"original_url":8,"source_id":9,"tags":10,"translations":27,"published_at":34,"created_at":35,"modified_at":36,"is_published":37,"publish_type":38,"image_url":14,"view_count":39},"b0183d10-bcfd-44ed-a178-a2c813f10b69","国家超算互联网AI社区上线Kimi K3:2.8万亿参数MoE一键调用,开源大模型有了国产算力底座","7月28日,国家超算互联网AI社区正式上线Kimi K3开源模型及API调用服务。企业和开发者可通过API一键调用、快速下载2.8万亿参数MoE模型文件并部署。超算互联网作为国产算力底座首次接入全球最大参数级别的开源大模型。","## 一、从开源发布到算力上线:48小时内的国产大模型新链路  7月27日晚,月之暗面正式开源了Kimi K3模型权重和技术报告,并同步释放支撑K3训练的三大基础设施:MoonEP、FlashKDA、AgentEnv。仅隔一天,7月28日国家超算互联网AI社区就宣布上线K3相关模型及API调用服务——企业和开发者可以通过API一键调用、下载2.8万亿参数的模型文件并完成本地化部署。  这种发布即接入的48小时链路,在过去两年的国产开源大模型节奏里并不常见。它意味着:模型从训练完成到开发者能够零门槛调用,中间的工程化交付鸿沟被国家超算互联网直接填掉了。  ## 二、超算互联网在做什么  国家超算互联网由科技部主导,2024年正式上线,整合了14个省市、超过30家国家级超算中心与智算中心的异构算力,是目前国内规模最大的算力调度网络。其AI社区模块的核心卖点是集算力、数据、模型三要素为一体——开发者不需要自己买卡、组集群、拉专线,就能直接在社区里获取算力、下载开源模型、跑训练或推理任务。  此次接入K3后,超算互联网实际上把全球最大参数级别开源MoE模型的算力底座拿到了国产手里。这一点比开源K3权重本身更具战略意义:权重谁都能下,但2.8万亿参数MoE要真正跑起来,对推理硬件、显存带宽、分布式并行框架的要求极高,普通中小企业几乎不可能独立承担。  ## 三、Kimi K3到底是什么  Kimi K3的核心数据点:  - **参数量**:2.8万亿总参数(MoE架构),激活参数未公开 - **架构**:基于KDA混合线性注意力机制(Kimi Delta Attention)+ 注意力残差(Attention Residuals) - **上下文窗口**:100万token - **多模态**:原生支持视觉理解 - **API定价**:输入3美元\u002F百万token,输出15美元\u002F百万token  KDA是月之暗面自研的注意力架构,目标是在长上下文场景下平衡效率与精度。叠加注意力残差保留前序注意力权重,K3在长程编程、知识工作、复杂推理场景下展现出了明显进步——官方演示显示K3能连续48小时自主调度EDA工具完成芯片设计、调用20+子智能体并行分析391个引力波事件。  ## 四、行业影响  1. **国产开源大模型的最后一公里被填平**。过去DeepSeek、Qwen等开源模型发布后,开发者卡在下载权重、配置环境、找算力跑推理三道坎上。超算互联网AI社区把这三道坎直接合并成一键API调用,这是国产算力+国产模型+国产平台第一次形成完整闭环。  2. **对闭源模型定价形成新一轮压力**。K3的API定价已经比Claude、GPT系列低一个数量级。当这个价格还能在国产算力底座上稳定运行,对闭源厂商的定价权冲击会非常直接。  3. **Agent和长上下文赛道的算力门槛被拉低**。2.8万亿参数、100万上下文的模型在小企业手里跑起来,意味着Agent类应用(特别是长程编码、知识工程类)的开发门槛从有大厂资源降到了有API Key。  ## 五、所以呢  对开发者来说,这是一个明显的行动信号:**国产开源大模型从能用进入了敢用、好用、便宜用的新阶段**。K3权重开源加上超算互联网AI社区的算力底座,让中小企业第一次能在不签云厂多年合约、不部署GPU集群的前提下,用上全球最大参数级别的开源MoE。  对行业来说,这件事的真正信号是国家算力调度网络开始和头部模型厂商形成**双向奔赴**——模型给得动,算力接得住,应用跑得起来。下一阶段值得关注的,是GLM、DeepSeek、Qwen等是否会以同样模式接入超算互联网,以及超算互联网能否在API稳定性、SLA、计费透明度上做到接近一线云厂的水平。  开源大模型的竞争,已经不只是参数和benchmark了,**算力底座的可用性**才是真正的护城河。","https:\u002F\u002Fwww.scnet.cn\u002Fhome\u002Fsubject\u002Fhxjd\u002Findex.html","e5d91fbf-bb6d-4e6b-82c0-760a5037dd59",[11,15,18,21,24],{"id":12,"name":13,"slug":13,"description":14,"color":14},"fca9258a-9430-455a-b95d-b9fae5e373a8","ai-inference",null,{"id":16,"name":17,"slug":17,"description":14,"color":14},"a8002d98-9df1-4ab9-94d4-a7625af634c4","china-ai",{"id":19,"name":20,"slug":20,"description":14,"color":14},"01598627-1ea6-4b27-a5d8-874971571a71","llm",{"id":22,"name":23,"slug":23,"description":14,"color":14},"7e89b5cc-57db-4f37-bc6d-28919a73931c","model-release",{"id":25,"name":26,"slug":26,"description":14,"color":14},"b9bd9039-fcdb-41a8-b85b-fc1587def2b9","open-source",[28],{"id":29,"lang":30,"title":31,"summary":32,"content":33},"de15446c-47cf-40ac-a557-10031cd11116","en","China's National Supercomputing Internet adds Kimi K3 to AI Community: 2.8T-parameter MoE, one-click API call, an open-source LLM with a domestic compute base","On July 28, China's National Supercomputing Internet AI Community launched Kimi K3 model and API services. Enterprises and developers can one-click call, download and deploy the 2.8T-parameter open-source MoE model via API. As a domestic compute base, the Supercomputing Internet has for the first time integrated the world's largest open-source LLM.","## 1. From open-source release to compute launch: a new domestic-LLM link in 48 hours  On the evening of July 27, Moonshot AI officially open-sourced the Kimi K3 model weights and technical report, alongside three pieces of training infrastructure: MoonEP, FlashKDA, and AgentEnv. Just one day later, on July 28, China's National Supercomputing Internet AI Community announced that K3-related models and API services had gone live—enterprises and developers can now one-click call, download and locally deploy a 2.8-trillion-parameter model via API.  This kind of release-to-deploy-in-48-hours pipeline is rare in the cadence of Chinese open-source LLMs over the past two years. It means the engineering-delivery gap between a finished training run and a zero-friction developer experience has been directly bridged by the National Supercomputing Internet.  ## 2. What the Supercomputing Internet actually does  Led by China's Ministry of Science and Technology and launched in 2024, the National Supercomputing Internet integrates more than 30 national supercomputing and intelligent computing centers across 14 provinces, making it the country's largest heterogeneous compute scheduling network. Its AI Community module is built around three pillars: compute, data, and models—so developers no longer need to buy GPUs, set up clusters, or lease dedicated lines; they can grab compute, download open-source weights, and run training or inference directly inside the community.  With K3 onboard, the Supercomputing Internet has effectively anchored the world's largest open-source MoE model on a domestic compute stack. That's more strategically significant than open-sourcing K3 weights itself: weights are downloadable by anyone, but running a 2.8T-parameter MoE in production demands extreme inference hardware, memory bandwidth, and distributed-parallel frameworks—things ordinary SMEs cannot realistically afford on their own.  ## 3. What Kimi K3 actually is  Key technical data points: - **Parameters**: 2.8T total (MoE architecture); activated-parameter count not disclosed - **Architecture**: KDA hybrid linear attention (Kimi Delta Attention) + Attention Residuals - **Context window**: 1M tokens - **Multimodal**: native visual understanding - **API pricing**:  \u002F 1M input tokens, 5 \u002F 1M output tokens  KDA is Moonshot's in-house attention architecture aimed at balancing efficiency and accuracy on long-context workloads. Combined with Attention Residuals—preserving prior attention weights—K3 shows notable gains on long-horizon coding, knowledge work, and complex reasoning. Moonshot's demos show K3 orchestrating EDA tools autonomously for 48-hour continuous chip design, and running 20+ sub-agents in parallel to analyze 391 gravitational-wave events.  ## 4. Industry implications  1. **The last mile for Chinese open-source LLMs is being paved.** In the past, after DeepSeek, Qwen and others open-sourced weights, developers were stuck on three hurdles: downloading weights, configuring environments, and finding compute. The AI Community collapses all three into one-click API call—the first time a Chinese compute + Chinese model + Chinese platform loop has fully closed.  2. **A new round of pricing pressure on closed-source models.** K3's API pricing is already an order of magnitude below Claude and GPT-tier offerings. Once that price point can run stably on a domestic compute base, the pricing leverage of closed-source vendors will be hit directly.  3. **Compute barriers in the Agent and long-context race are being lowered.** A 2.8T-parameter, 1M-context model now runnable by small businesses means the development threshold for Agent applications—especially long-horizon coding and knowledge engineering—drops from you need big-tech resources to you need an API key.  ## 5. So what  For developers, this is a clear call to action: **Chinese open-source LLMs have moved from usable to reliable, friendly, and cheap-to-use.** With K3 open-sourced and a domestic compute base to run it on, SMEs can now access the world's largest open-source MoE without multi-year cloud contracts or in-house GPU clusters—no small thing.  For the industry, the real signal here is that the national compute scheduling network and top-tier model vendors are starting a **two-way convergence**: models can be released, compute can pick them up, and applications can actually run. The next things to watch are whether GLM, DeepSeek and Qwen onboard the same way, and whether the Supercomputing Internet can match Tier-1 cloud providers on API stability, SLAs, and billing transparency.  Open-source LLM competition is no longer just about parameters and benchmarks—**the usability of the compute base is the real moat**.","2026-07-28T09:30:00Z","2026-07-28T08:10:31.526401Z","2026-07-28T08:10:31.526410Z",true,"agent",2]