Introduction to Foundry Local

Foundry Local is a Microsoft solution that brings the power of Azure AI directly to your local environment. It allows developers to run AI models entirely on their own infrastructure—whether that is a desktop computer, laptop, or personal server. With Foundry Local, AI inference happens on-device, eliminating the need for cloud connectivity while maintaining enterprise-grade security.

This approach makes Foundry Local a practical choice for developers who want privacy, cost efficiency, and greater control over how and where AI models are executed.

What Is Foundry Local?

Foundry Local is a free, on-device AI inference solution from Microsoft. It enables developers to run large language models (LLMs) and other AI models locally without requiring an Azure subscription or incurring any cloud billing costs.

The platform supports multiple integration options, including:

• Command Line Interface (CLI)

• SDKs

• REST APIs

These interfaces make Foundry Local flexible enough to integrate into different development workflows and applications.

Key Benefits of Running AI Models Locally

Running AI models locally with Foundry Local offers several advantages:

Privacy

All prompts and queries remain within your local system. No data is sent to external servers, making it suitable for sensitive or confidential workloads.

Performance

Performance depends on your hardware configuration. Foundry Local can leverage CPUs, GPUs, and NPUs, allowing you to maximize inference speed based on your available infrastructure.

Cost Savings

Because models run locally, there are no cloud usage fees, subscriptions, or billing concerns. You only use your own hardware resources.

Customization

Developers have full control over which models are used, how they are configured, and how they are integrated into applications.

Supported Platforms and Installation Options

Foundry Local supports multiple operating systems and development environments:

• Windows: Installed using the winget package manager

• macOS: Installed using Homebrew (brew)

• SDKs available:

  • Python

  • JavaScript

  • C#

  • Rust

On Windows, installation is straightforward using the following command:

Once installed, Foundry Local becomes available as a command-line application.

Working with AI Models

Listing Available Models

After installation, you can view all available models using the CLI. The model list includes:

• Supported execution devices (CPU, GPU, NPU)

• Model size

• License information

• Model variants

This allows developers to choose models based on hardware capabilities and storage constraints.

Downloading and Running Models

Models can be downloaded to a local cache and loaded on demand. Once a model is loaded, Foundry Local provides an interactive chat mode where prompts can be entered directly.

Some common CLI commands include:

• foundry model list – List all available models

• foundry model info – Display detailed model information

• foundry model run – Load and run a model

• foundry model unload – Unload a running model

Interactive Chat Commands

While interacting with a model, several commands are available:

• /help – Display available commands

• Ctrl + C – Cancel the current generation

• /exit – Exit the interactive session

Understanding Model Limitations

Because Foundry Local runs models entirely offline, they do not have access to real-time data or external tools. As a result:

• Responses are limited to the model’s training data

• Real-time queries, such as current weather, cannot be answered accurately

• Response quality varies depending on the model size and training quality

These limitations are expected and reflect the trade-offs of running models locally rather than in the cloud.

Exploring Available Models

Foundry Local provides access to a wide range of AI models, which can be filtered and sorted by:

• Model family

• File size

• Execution device (CPU-only, GPU-enabled, etc.)

• Last updated date

Each model includes detailed metadata such as:

• Description

• License

• Owner

• Available variants

• Supported tasks

This makes it easy to evaluate and select the most appropriate model for a given use case.

Open Source and Community Support

Developers who want to explore the technical details behind Foundry Local can access its GitHub repository. There, they can review:

• Source code

• Release notes

• Contributors

• Ongoing development activity

This transparency supports customization and deeper integration for advanced users.

Conclusion

Foundry Local enables developers to run AI models directly on their own devices with complete data privacy, zero cloud costs, and flexible deployment options. Whether used on a laptop, desktop, or personal server, it provides a powerful way to experiment with and deploy AI locally.

With support for multiple platforms, SDKs, and a growing catalog of models, Foundry Local is a strong option for developers who want full control over AI inference without relying on cloud infrastructure.