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Earlier this week at GTC Taipei, NVIDIA unveiled the NVIDIA RTX Spark product family, including small form factor desktops and laptops built for the age of personal assistants. These desktops and laptops deliver 1 petaflop of AI power, up to 128 GB of memory, and CUDA-accelerated AI frameworks for running large models alongside everyday work.  Microsoft is creating an RTX Spark special developer edition—the Microsoft Surface NVIDIA RTX Spark Dev Box—preloaded with a modified Windows configured for developers and the top developer tools you need to get started. To learn more, see Building the n

One popular way to run AI locally has been to use multiple GPUs to access more memory and compute. While cloud frameworks like vLLM are well optimized for multiple GPUs thanks to their use in data centers, PC frameworks like llama.cpp and the ComfyUI implementation in PyTorch are not optimized for it. To solve this challenge, NVIDIA has collaborated with both llama.cpp and ComfyUI to enhance performance for RTX PCs with two equivalent GPUs. This enables you to run larger models and use the compute of both GPUs for better performance. llama.cpp now supports tensor parallelism (TP), fully utiliz

NVIDIA NemoClaw for building autonomous AI agents now supports all NVIDIA client systems—GeForce RTX, NVIDIA RTX PRO, NVIDIA DGX Spark, and NVIDIA DGX Station for Windows—through Linux and Windows Subsystem for Linux (WSL). This enables you to easily set up and sandbox an agent, with optimized local models handpicked for your hardware. The update also includes enhancements to the installer to make it easier and more seamless. NemoClaw also now supports running Hermes Agent as an option.  This week, Hermes Agent also released native Windows support, including both a command-line interface, alon