--- 格式版本: 2 标题: "Compatible Moonshot AI Kimi Models" 原文链接: "https://docs.oracle.com/iaas/Content/generative-ai/imported-moonshot-ai-models.htm" 发布日期: "2026-09-04" 发布时间校准状态: "found" 发布时间需复核: "否" 发布时间来源: "rule:local:strict_original_body" 发布时间证据: "Updated 2026-09-04" 发布时间校准原因: "规则确认唯一严格发布时间，来源 local:strict_original_body" 发布时间校准置信度: "high" 发布时间候选数量: 8 发布时间严格候选数量: 1 发布时间原页读取状态: "source template page reused from URL open" 发布时间未找到原因: "" 发布时间校准时间: "2026-09-06T18:20:42+08:00" 发布时间仲裁状态: "skipped" 发布时间仲裁尝试次数: 0 发布时间仲裁耗时毫秒: 0 发现时间: "2026-09-06T17:43:35+08:00" 入库时间: "2026-09-06T10:26:46.295Z" 来源平台: "固定入口" 搜索渠道: "fixed_url" 搜索词: "https://docs.oracle.com/en-us/iaas/releasenotes" 匹配关键词: - "AI" 相关厂家: - "Oracle" 相关专家: [] 内容类型: "网页" 抓取工具: "Jina Reader" 清洗工具: "Jina Reader Markdown + Defuddle/Readability 正文提取" 原始附件: [] AI优质: "否" AI打分: 33 AI分档: "非优质" AI质检状态: "不通过" AI打分理由: "正文主线为Oracle OCI Generative AI导入Moonshot Kimi模型（Kimi-K3、K2.6、K2.7-Code）的兼容性文档，属云上模型托管/部署说明，而非超节点、AI Rack、rack-scale或关键部件基础设施；主体是第三方LLM接入，非机架级AI基础设施。来源为Oracle官方文档，权威性尚可，但页面是导航/文档壳，仅含少量硬件shape信息和计费说明，未提供模型架构、互连、供电、液冷或部署细节，也没有Kimi K3本身的新架构事实。历史知识库未见Kimi-K3超节点/机架级信息，但本文新增主要是OCI模型兼容列表，不具备业务库价值。按硬否决规则（应用与模型效率/教程运维）应判false。" AI质检模型: "zj-deepseek-v4-flash" AI质检时间: "2026-09-06T18:27:02+08:00" AI主题相关性: 2 AI来源权威性: 12 AI新颖性: 5 AI技术细节: 5 AI商业部署信号: 5 AI完整性: 4 AI评分提示词版本: "v17-精简生产版" AI评分提示词SHA256: "48fb9777f386026761b4873eaff30807694fb11e9b352d7c69bf2dfde750cc7d" AI评分知识库版本: "knowledge_base_v1-20260819+runtime.96" AI评分知识库SHA256: "0cae74ad2e30b227036c5952745542146844722958bc01868bbd0799ab59eeec" AI评分知识库检索词: "[\"Oracle\",\"https://docs.oracle.com/en-us/iaas/releasenotes\",\"RAS\",\"Meta\",\"moonshotai/Kimi-K3\",\"URL\",\"K3\",\"US\",\"UK\",\"EU\",\"OCI\",\"OHPPanel1nav0625\"]" AI评分知识库命中: "[{\"id\":\"runtime-dccd09f98e2ca028070793f0\",\"title\":\"https://blogs.oracle.com/cloud-infrastructure/oci-achieves-nvidia-exemplar-cloud\",\"sourceType\":\"ai_excellent_article\",\"time\":\"\",\"matchedTerms\":[\"Oracle\",\"RAS\",\"US\",\"OCI\"],\"rank\":-14.837368732299874},{\"id\":\"runtime-66d1ddc58948150bffee973a\",\"title\":\"Delivering Vera: NVIDIA’s First CPU Built for Agents Is Shipping Now\",\"sourceType\":\"ai_excellent_article\",\"time\":\"\",\"matchedTerms\":[\"Oracle\",\"RAS\",\"US\",\"EU\",\"OCI\"],\"rank\":-12.721267641322296},{\"id\":\"runtime-0210d17c29c694da454d0e78\",\"title\":\"HPE caps stellar Q3 with Oracle ‘gigawatt scale’ networking deal\",\"sourceType\":\"ai_excellent_article\",\"time\":\"\",\"matchedTerms\":[\"Oracle\",\"RAS\",\"US\",\"OCI\"],\"rank\":-11.330849148820414},{\"id\":\"july-correct-0018\",\"title\":\"AMD, Cerebras partner on joint Helios rack-scale AI inference platform\",\"sourceType\":\"labeled_article\",\"time\":\"2026-07\",\"matchedTerms\":[\"Oracle\",\"RAS\",\"Meta\",\"URL\",\"US\",\"EU\"],\"rank\":-11.25286703895051},{\"id\":\"july-correct-0112\",\"title\":\"超前点映AMD Advancing AI 2026：AMD AI YES？-36氪\",\"sourceType\":\"labeled_article\",\"time\":\"2026-07\",\"matchedTerms\":[\"Meta\",\"URL\",\"K3\",\"US\",\"UK\",\"EU\"],\"rank\":-10.949818948670375}]" 采集批次: "2026年9月6日17点41分46秒" 采集批次ID: "20260906-174146-0dbc83f7" 去重键: "https://docs.oracle.com/iaas/Content/generative-ai/imported-moonshot-ai-models.htm" --- Title: Compatible Moonshot AI Kimi Models URL Source: https://docs.oracle.com/iaas/Content/generative-ai/imported-moonshot-ai-models.htm Markdown Content: * [Oracle Cloud Infrastructure Cloud Adoption Framework](https://docs.oracle.com/en-us/iaas/Content/cloud-adoption-framework/home.htm) * [Getting Started](https://docs.oracle.com/en-us/iaas/Content/GSG/Concepts/baremetalintro.htm) * [Oracle Cloud's Free 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Updated 2026-09-04 [Skip to main content](https://docs.oracle.com/iaas/Content/generative-ai/imported-moonshot-ai-models.htm#dcoc-content-body) Updated 2026-09-04 # Compatible Moonshot AI Kimi Models You can import large language models from Hugging Face and OCI Object Storage buckets into OCI Generative AI, create endpoints for those models, and use them in the Generative AI service. **Note** Before selecting a model, review the guidance following the model tables on this page for selecting a compatible hardware unit shape and understanding billing for dedicated AI clusters that host imported models. ## Kimi🔗 The Kimi K2.6 and Kimi K2.7 Code models are optimized for long-horizon coding, agentic workflows, and complex software engineering tasks. Kimi K2.6 is designed for coding, coding-driven design, autonomous execution, and task orchestration, while Kimi K2.7 Code is a coding-focused model built on Kimi K2.6 for long-horizon software engineering workflows. Compatible Kimi Models| Hugging Face Model ID | Model Capability | Minimum Dedicated AI Cluster Unit Shape | | --- | --- | --- | | [moonshotai/Kimi-K3](https://huggingface.co/moonshotai/Kimi-K3) | IMAGE_TEXT_TO_TEXT | * B300_X8 * B200_X16 * H100_X32 | | [moonshotai/Kimi-K2.6](https://huggingface.co/moonshotai/Kimi-K2.6) | TEXT_TO_TEXT | * H200_X8 * B200_X8 | | [moonshotai/Kimi-K2.7-Code](https://huggingface.co/moonshotai/Kimi-K2.7-Code) | TEXT_TO_TEXT | * H200_X8 * B200_X8 | **Note** For Kimi K3, the `H100_X32` unit shape is available in the US Midwest (Chicago) and Japan Central (Osaka) regions, and the `B200_X16` unit shape is available in the UAE Central (Abu Dhabi) region. Multi-node serving is also available in the UAE Central (Abu Dhabi) and Japan Central (Osaka) regions. **Important** * For imported models, you can use the native context length specified by the model provider. However, the effective maximum context length is limited by the underlying hardware setup that you select for the hosting dedicated AI clusters in OCI Generative AI. To take full advantage of a model's native context length, you might need to provision more hardware resources. * Use the fine-tuned models only if they match the compatible base model's transformer version and have a parameter count within ±10% of the original. * To decide where you can host an imported model, find a compatible unit shape for the model in the table on this page, and then confirm that the hardware shape is available in the target region in [Hardware Unit Shapes by Region](https://docs.oracle.com/iaas/Content/generative-ai/hardware-unit-shapes-by-region.htm#imported-model-shapes). A model can be hosted in a region only when the region provides a hardware shape listed for that model. * For steps on how to deploy the imported models, see [Managing Imported Models](https://docs.oracle.com/iaas/Content/generative-ai/manage-imported-models.htm#imported-models "In addition to using the hosted pretrained models in OCI Generative AI, you can import validated open source and third-party models (for example, from Hugging Face) into OCI Generative AI, host them, create endpoints, and use them like any other model."). **Note** **Billing for Dedicated AI Clusters Hosting Imported Models** Dedicated AI clusters that host **imported models** don't require the 744-unit-hour minimum commitment that applies to dedicated AI clusters hosting pretrained models available in OCI Generative AI. Instead, an imported-model dedicated AI cluster has a minimum billable duration of one hour. For example, a cluster that uses one AI unit and runs for 30 minutes is billed for one AI unit-hour. After the first hour, charges are based on the cluster's actual running time and are prorated to the millisecond. For example, a cluster that runs for one hour and one minute is billed for that duration, rather than for two full hours. OCI sends usage records to Metering and Billing every five minutes while the cluster is running. If the cluster is deleted before the one-hour minimum is reached, OCI continues reporting billable usage until the minimum is met. If the cluster runs for more than one hour, OCI continues sending usage records every five minutes until the cluster is deleted. 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