Using GitHub Copilot CLI with Azure AI Foundry (BYOK Models) – Part 2

In Part 1 , you ran GitHub Copilot CLI against a local model using LM Studio. That setup gives you control. No external calls. No data leaving your machine. But it comes with clear limits. Small models struggle, and output quality drops fast on anything non-trivial. This is where Azure AI Foundry comes in. Instead of running models locally, you connect Copilot CLI to a cloud-hosted model you control. You still use the same BYOK (Bring Your Own Model) approach, but now the model runs on Azure. That changes the trade-offs: You gain better models and stronger reasoning You keep control over the endpoint and deployment You accept cost and network dependency This is not a replacement for the local setup. It is the next step if you want privacy but at the same time, more power. Setting Up Azure AI Foundry This is the only "Azure-heavy" part. Keep it minimal. You just need a working endpoint and a deployed model. 1. Create or Use an Existing Resource Go to Azure AI Foundry in the Azure portal