Build Personal AI Agents on Windows PCs with New Tools from Microsoft and NVIDIA | NVIDIA Technical Blog

This post details the introduction of secure agent sandboxing on native Windows using Microsoft eXecution Containers (MXC) and NVIDIA OpenShell. It highlights performance improvements for agentic inference through optimizations in llama.cpp (Multi-Token Prediction, Programmatic Dependent Launch) and vLLM, achieving up to 2.6x throughput gains. The post also introduces multi-GPU support for RTX PCs via tensor parallelism in llama.cpp and LM Studio, and updates to agent capabilities with NemoClaw, Hermes Agent, and H Company's Holo 3.1 models, focusing on easier setup, native app integration, and GPU performance.