Hugging Face Models on Foundry Managed Compute

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.

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.

Hugging Face is the public square of open AI: 15 million builders, 400,000 organizations, and over 3 million open models published , with new frontier capabilities — agentic coding, video segmentation, speech, embeddings — landing weekly. It's the GitHub of open models, where the community publishes weights, writes model cards, compares evaluations, and pulls models for experimentation.

Because weights are pre-staged in Azure storage and runtime images live in a Microsoft-managed registry, your deployments won't need outbound network access to Hugging Face Hub — you can deploy to production inside a private network.

On the roadmap: broader coverage of the Hugging Face ecosystem, additional accelerator families, and Bring Your Own Weights for fine-tuned and proprietary variants deployed through the same templates and governance as Collection models.

Same code, same workflow. Quota is aligned to accelerator families, so a plan built on the H100 family today carries forward as new hardware generations come online.

The catch has always been the operational layer: discovery, license review, security screening, runtime selection, GPU sizing, image building, CVE patching, and standing the model up behind an enterprise-grade endpoint. Hugging Face, by itself, is not an enterprise serving platform. Hugging Face models on Foundry is that operational layer, run by Microsoft.

SGLang — a serving engine for language and multi-modal models, with strong support for structured outputs (JSON, regex, grammar-constrained generation) that agentic and tool-using workloads depend on. Hugging Face and the SGLang team have built a Transformers backend integration for SGLang, so any model in the Transformers library runs on SGLang out of the box — and reaches Foundry the same day it lands on Hugging Face.

Available now in preview: the Hugging Face Collection in the Microsoft Foundry Model Catalog — thousands of models across every modality, refreshed weekly, deployable onto Foundry Managed Compute with NVIDIA A100, NVIDIA H100, or AMD MI300X accelerators in Global and Data Zone scopes, behind a unified Foundry endpoint with Playground support, first-class Azure Monitor metrics, per-deployment billing tags, and curated runtime upgrades and CVE patching applied automatically to your deployments.

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.

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: