When leveraging agents, developers need both choice and control. They need technologies that offer clear boundaries for their agents and make it easy to choose the model with the right speed, performance, and cost profile for each task. That’s why GitHub offers frontier models from major model providers, as well as options like Project HydraFusion, an orchestrator choosing one or multiple models for each task while balancing performance, cost, and latency. It’s also why Windows has developed Microsoft Execution Containers (MXC) to help secure interactive and non-interactive agentic coding sessions.
Coming by the end of the month, GitHub Copilot will determine when a task is best handled by on-device intelligence and when it should leverage cloud-scale models. Rather than forcing developers to manage infrastructure decisions themselves, GitHub Copilot automatically coordinates local and cloud inference behind the scenes. For NVIDIA RTX Spark Windows PCs like Surface Laptop Ultra, that means we are enabling local coding in GitHub Copilot with powerful local inference models and hardware capable of delivering a great experience at the edge.
The result is poised to be the next step in the HydraFusion vision: intelligent orchestration that spans not just multiple models, but multiple compute environments including the edge. GitHub Copilot can run commands in these environments with controlled access to files, networks, system capabilities, and credentials. Developers can automate with confidence and security in mind.
Source: https://commandline.microsoft.com/local-models-sandboxed-tools-github-windows/