Hugging Face模型在Foundry托管计算上可用

At Microsoft Build 2026, we announced Foundry Managed Compute and Hugging Face models on Foundry — a curated catalog of open-weight models from the Hugging Face ecosystem, refreshed weekly, deployable in one click onto Foundry Managed Compute. Weights are pre-staged in Azure, runtimes are built and scanned by Microsoft, and every model in the Collection ships with the same enterprise security, governance, observability, and billing that applies to every other model on Foundry. Microsoft Foundry is a platform for building and operating agentic AI applications. Foundry starts with the widest model selection on any cloud — models from Microsoft, OpenAI, Anthropic, Meta, Mistral, DeepSeek, Hugging Face, and others, spanning frontier, open-source, and custom weights — all accessible through a single endpoint and a single set of SDKs in Python, C#, JavaScript, and Java. On top of those models sits the Foundry Agent Service : multi-agent orchestration with built-in memory, knowledge grounding through Foundry IQ, and a catalog of connectable tools via agentic protocols, so agents can work with enterprise data. Once agents are running, Foundry provides end-to-end tracing, real-time monitoring, continuous evaluations, and a prompt optimizer that improves agent behavior based on eval results — observability and quality loops that are part of the platform. Alongside that, developers get access to: An AI Red Teaming Agent for adversarial testing Azure Policy integration directly within the platform Alongside pay-per-token (lowest-friction path to get started) and provisioned throughput (predictable, high-performance production workloads on frontier models), Foundry Managed Compute is the third deployment option in Foundry: a managed GPU platform-as-a-service for open-source and custom models. You deploy a model instance described by the things that matter to your workload — parameter count, context length, and whether you want to optimize for latency or throughput — and Foundry handles the GPU topology underneath, whether the instance lands on one accelerator or several, so you think and plan in model terms. Microsoft takes care of the machine: container updates, runtime upgrades, and security patches happen automatically on the supported runtimes — vLLM, SGLang, TensorRT-LLM, NIM, TEI, llama.cpp — without redeploying your model, while model configuration, deployment behavior, and routing stay with you. That consistency carries through the developer surface — pay-per-token, provisioned throughput, and Managed Compute share: Open-source models integrate with Foundry Agents the same way frontier models do, so you can mix model types in a single agent without a separate integration path. Global deployments — broadest capacity and best pricing