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About

NVIDIA Personal AI Router (PAIR) is a tool that connects compatible Windows, Linux, and macOS systems into a personal AI inference cluster and routes AI app and agent workloads through a single local endpoint. It brings together RTX, DGX Spark, and Mac systems already on the same network, helping them work as one local AI cluster without special cables, racks, or complex cluster setup. PAIR discovers compatible machines and distributes inference requests across available nodes, allowing busy AI workflows to tap into idle compute regardless of the node’s operating system. It works alongside familiar local inference backends, with support for Ollama and LM Studio, giving applications a consistent endpoint while intelligently proxying requests to available local compute. PAIR is built for private local inference, so prompts, files, and agent context stay on the user’s local network instead of being sent to a cloud inference service.

About

NVIDIA Nemotron 3.5 Bolt is a family of open artificial intelligence models designed for local AI agents, autonomous task execution, and conversational applications. The family includes Nemotron 3.5 Bolt 74B-A9B, a 74-billion-parameter mixture-of-experts model with approximately 9 billion active parameters, and Nemotron 3.5 Bolt E4B, a compact model optimized for conversational agents. The 74B-A9B variant uses native 2-bit quantization to operate within approximately 24GB of memory on compatible NVIDIA hardware. Its agentic capabilities support web research, software development, code debugging, and multistep task automation without requiring cloud-based inference. The E4B variant targets local voice assistants, interactive characters, and embedded applications with a 4GB memory footprint. Nemotron 3.5 Bolt supports deployment on NVIDIA RTX systems, DGX Spark, and other compatible hardware, giving developers greater control over inference, application data, and local AI workflows.

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Not Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Supported
Cloud Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

AI developers, enthusiasts, and power users seeking to distribute private local AI inference across multiple compatible computers through a single endpoint

Audience

AI developers, software engineers, machine learning researchers, game developers, robotics engineers, enterprise IT teams, and organizations building local autonomous agents, coding assistants, conversational AI systems, and privacy-conscious applications on NVIDIA hardware

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Not Supported

API

Offers API Not Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Pricing

Free
Free Version Supported
Free Trial Not Supported

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

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Reviews/Ratings

Overall 5.0 / 5
features 5.0 / 5

Pros & Cons from Real Users

Pros

  • What I like most is that I can run a genuinely capable agent model locally without needing datacenter hardware. The 74B-A9B version fits in 24GB of memory, which makes it realistic for high-end RTX systems and DGX Spark. It is also surprisingly useful for real agent work. I can use it for research, coding, debugging, writing, and multi-step tasks while keeping everything on my own machine instead of pushing code or sensitive data to a cloud API. The performance-to-memory tradeoff is probably the biggest win. NVIDIA says Bolt 74B-A9B is the #1 open model in its class on PinchBench and #2 on BrowseComp, so it is not just small enough to run locally — it is actually competitive at agentic tasks.

Cons

  • The main downside is that 24GB is still a meaningful hardware requirement, and local inference will not always match the raw capability of the biggest cloud frontier models.

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

NVIDIA
Founded: 1997
United States
www.nvidia.com/en-us/ai-on-rtx/personal-ai-router/

Company Information

NVIDIA
Founded: 1993
United States
nvidia.com

Alternatives

Alternatives

Macyou

Macyou

Macyou LLC

Categories

Categories

Integrations

Baseten Not Supported
Hugging Face Transformers Not Supported
LM Studio Supported
NVIDIA NIM Not Supported
Ollama Supported
OpenRouter Not Supported
vLLM Not Supported

Integrations

Baseten Supported
Hugging Face Transformers Supported
LM Studio Not Supported
NVIDIA NIM Supported
Ollama Not Supported
OpenRouter Supported
vLLM Supported
Claim NVIDIA Personal AI Router (PAIR) and update features and information
Claim NVIDIA Personal AI Router (PAIR) and update features and information
Claim Nemotron 3.5 Bolt and update features and information
Claim Nemotron 3.5 Bolt and update features and information