AI agents are learning to do more by working together. A lead agent can break a complex task into smaller jobs and assign those jobs to specialized subagents. Additionally, users are starting to run multiple agent sessions at the same time. Multi-agent workflows for accomplishing complex tasks are also becoming more common.
This breadth-first approach can improve the speed of task completion and improve the quality of responses, but it can also bottleneck the system as many requests are sent to the GPU simultaneously.
NVIDIA Personal AI Router (PAIR) leverages your local hardware to relieve this multi-agent and subagent bottleneck. PAIR routes each independent inference request to an available system on the home network. It works with familiar local inference services, including Ollama and LM Studio, so users can expand the compute available to an agent without redesigning the agent itself. No agent harness changes are necessary.
The NVIDIA PAIR beta is available for supported Windows, macOS, and Linux systems through graphical and terminal interfaces. It supports compatible systems with NVIDIA GeForce RTX 20 Series GPUs and newer, NVIDIA RTX PRO workstation GPUs (Turing architecture and newer), as well as NVIDIA DGX Spark and Apple M4+ silicon.
