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大模型 cloud.google.com ·

Google Cloud 将 OpenAI 模型引入 Model Garden,扩展企业模型选择

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Google Cloud 官方博客称已在 Model Garden 上线 OpenAI 模型,包括面向编码、计算机使用、专业任务与科研的 GPT-Astra,成本更低的 GPT-6.1 Sol,以及面向日常规模化工作的 GPT-6 Luna。客户可通过 Google Cloud Marketplace 统一计费并抵扣云承诺与 FSP,平台宣称提供数据边界、隔离网关、统一审计与身份管理,ZDR 与 Confidential Compute 为即将推出。

AI推荐理由 Google Cloud 官方博客宣布在 Model Garden 上线 OpenAI 模型,并称成为唯一同时提供三家头部闭源 LLM 的超大规模云厂商;正文给出 GPT-Astra、GPT-6.1 Sol、GPT-6 Luna 的定位、通过 Marketplace 统一计费与承诺抵扣、数据边界与审计等企业治理细节,信息密度高且来源为官方。局限是模型能力仅有厂商自述定位,缺少独立评测或价格数据,部分安全能力(ZDR、Confidential Compute)标注为即将推出。

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Google Cloud has always been defined by choice, enterprise-grade governance, and market-leading price-performance. Key to the foundation of openness and choice is giving customers flexibility to run agentic workloads across their choice of models and infrastructure to achieve the right balance of cost, capability, and performance. Today, we are expanding that foundation by launching OpenAI models in Google Cloud’s model garden. Google Cloud is now the only hyperscale cloud provider offering access to all three leading closed source LLMs, alongside more than 200 first-party, third-party, and open models on a unified enterprise AI platform. The right model for every workload Modern enterprise AI requires matching each workload to the right model rather than relying on a single model for every task. By adding OpenAI’s newest models to model garden, we are giving teams options across the full spectrum of enterprise workloads. For OpenAI models: GPT-6 Astra: Designed for demanding work across coding, computer use, professional tasks, and scientific research. GPT-6.1 Sol: Near-Astra intelligence at lower cost across agentic coding, computer use, and professional work. GPT-6 Luna: A fast, cost-efficient model for everyday work at scale. Using the platform, customers can dynamically select and swap the optimal model for any use case based on performance, latency, and cost efficiency without architectural lock-in or separate vendor contracts. Developers gain the freedom to build with hundreds of choices in model garden. Because OpenAI models are transacted directly through Google Cloud Marketplace, all usage appears on a single Google Cloud invoice, draws down existing cloud commitments, and counts toward Flexible Savings Plans (FSP) across model providers. Built-in data governance and enterprise security Scaling generative AI should never require compromising on compliance or security. Built from the ground up for enterprise governance, the Gemini platform is trusted by leading global organizations today. We ensure that running any third-party or OpenAI workload meets the most rigorous enterprise standards: Strict data perimeters: Customer prompts, context, and outputs remain entirely within your designated data perimeter and are never used to train foundation models, with Zero Data Retention (ZDR) options available coming soon. Isolated access boundaries: OpenAI models run on dedicated Google Cloud infrastructure with Confidential Compute coming soon. All queries are routed through hardened, isolated gateways, ensuring data transit remains strictly within Google Cloud's secure environment and third-party model providers have no unauthorized access to your cloud environment. Unified auditing and identity: Every agent and model interaction operates under an authenticated identity, giving IT administrators end-to-end visibility, VPC Service Controls protection, and unified audit logging across their entire enterprise footprint. Getting started OpenAI’s GPT-6 Astra, GPT-6.1 Sol, and GPT-6 Luna models are rolling out now in private preview to select enterprise customers in Google Cloud’s model garden, with more coming soon. Starting today, customers can build with these models through our APIs and connect their local Codex CLI and Desktop workflows directly to our Gemini platform for inference. Please use this form to express interest. Coming soon, OpenAI models will be available in Google Cloud’s Gemini for business and Google Antigravity, providing enterprise customers and developers with model choice flexibility and the best model for each task.

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