Microsoft and Meta team up to bring Llama 2 to Azure and Windows

Llama 2 is Meta’s newly updated family of open large language models, spanning 7B, 13B, and 70B parameter versions. Unlike its predecessor, this generation comes with commercial rights. Through a tight partnership with Microsoft, you can now deploy and fine-tune it in the cloud via Azure, or run it directly on a local Windows machine.

That means developers building generative AI features no longer have to choose strictly between proprietary cloud APIs and the headache of configuring open-source infrastructure from scratch.

What you can do and how to run it

In the cloud, Llama 2 is available inside the Azure AI model catalog, currently in public preview. The catalog acts as a turnkey hub that handles the underlying dependencies so you do not have to manage infrastructure setup manually.

Developers can test, evaluate, and fine-tune the 7B, 13B, or 70B models directly on Azure. It comes bundled with DeepSpeed and ONNX Runtime optimizations out of the box, which significantly cuts down the time required for model fine-tuning.

On the safety side, Microsoft integrated Meta's safeguards with its own Azure AI Content Safety service. When deploying via Azure AI, your models come with layered safety checks enabled by default. Teams can test models against custom sample datasets and combine meta-prompts with Retrieval Augmented Generation (RAG) to keep outputs reliable.

For those who prefer not to send sensitive data to the cloud, Llama 2 is also optimized for local execution on Windows. By targeting the DirectML execution provider through ONNX Runtime, developers can integrate generative capabilities directly into desktop applications.

The model assets can be accessed through its GitHub repository. With Windows Subsystem for Linux (WSL), supported Windows development tools like VS Code, and capable local GPUs, you can even handle model fine-tuning right on your local PC without touching a remote server.

Why it matters

If you are an engineer or an enterprise looking for a commercially viable alternative to closed APIs, Llama 2 on Azure and Windows gives you the best of both worlds. You get enterprise-grade deployment and safety rails on the cloud, plus the freedom to run edge workflows locally on PC hardware.

We think Microsoft's play here is genuinely clever. While backing OpenAI remains its headline strategy, huge swathes of corporate clients demand self-hosted models for compliance and cost reasons. By becoming Meta's preferred launch partner, Microsoft captures both camps inside the Azure and Windows ecosystem. Just keep in mind that running the 13B or 70B versions locally still requires hefty GPU muscle, so cloud-based experimentation is still the most realistic starting point for most teams.