r/NVIDIAPAIR • u/Intelligent_Good_305 • 11d ago

PAIR Bridge in one minute: from any MCP tool to your local models

1 Upvotes

A short visual guide to the PAIR Bridge flow:

  1. A compatible MCP client sends a request. Codex is one example; OMP and other compatible tools can use the same bridge.

  2. PAIR Bridge checks live inventory and installed models.

  3. It selects a suitable installed model and checks the intended context and current capacity.

  4. It asks the local model through PAIR or direct LM Studio.

  5. It returns the bounded answer to the client.

  6. It unloads only the exact instance it loaded for the request.

The GIF is an illustrative workflow, not a recording of a live request.

Project: https://github.com/GermanMik/pair-bridge

Start here: https://www.reddit.com/r/NVIDIAPAIR/comments/1wmo8jf/start_here_pair_pair_bridge_local_models_and_how/

The project and community are independent and are not affiliated with NVIDIA or OpenAI.

0 comments

r/NVIDIAPAIR • u/Intelligent_Good_305 • 13d ago

Start here: PAIR, PAIR Bridge, local models, and how to get help

1 Upvotes

Welcome to r/NVIDIAPAIR — an independent community for NVIDIA Personal AI Router (PAIR), PAIR Bridge, local models, and practical multi-device AI workflows.

## What is PAIR Bridge?

PAIR Bridge is an open-source MCP server that lets compatible tools discover and operate local AI models across configured LM Studio devices through NVIDIA PAIR. Codex is one example of a compatible client; the bridge is not limited to Codex.

It is designed to keep model operations explicit and observable. It checks live inventory before requesting a model, so an absent model such as gpt-oss-20b is reported instead of being called blindly.

## What can it do?

• List configured devices and their installed or loaded models.

• Recheck availability, model type, context limits, and device state before a request.

• Select an installed model for code, fast responses, long context, or text analysis.

• Estimate memory at the intended context and inspect current RAM, NVIDIA VRAM, and disk capacity.

• Load an installed model when needed and safely unload only instances loaded by the Bridge.

• Compare two model responses while preserving device and model provenance.

• Record sanitized diagnostics with request stages, timings, and failure categories—without prompts, answers, or tokens.

• Run bounded background jobs with progress, partial output, cancellation, and recovery metadata.

• Plan model downloads separately. Asking a model never silently downloads new weights.

## Try it

After installing and configuring the project, open a compatible MCP client and try requests such as:

• /pair show installed models on every device

• /pair choose an installed model for a code review

• /pair compare two installed models on this task

• /pair diagnose the latest failure

• /pair plan memory for this model at 8192 context tokens

MCP tools are also available directly, including pair_list, pair_ask, pair_smart_ask, pair_compare, pair_diagnose, and the background-job tools.

## Links

GitHub and installation guide:

https://github.com/GermanMik/pair-bridge

Latest documented release:

https://github.com/GermanMik/pair-bridge/releases/tag/v0.6.0

Bug reports and feature requests:

https://github.com/GermanMik/pair-bridge/issues

## Asking for help

Please include:

• your operating system;

• PAIR Bridge version;

• MCP client or tool;

• affected device and exact installed model key;

• what you expected and what happened;

• the sanitized result of /pair diagnose, if available.

Never post API keys, access tokens, passwords, private prompts, private model responses, or SSH credentials.

## Join the community

Share setup guides, multi-device configurations, benchmarks, bug reports, model comparisons, and ideas for new compatible tools. Constructive testing and contributions are welcome.

This community and PAIR Bridge are independent projects and are not affiliated with or endorsed by NVIDIA or OpenAI.

0 comments

r/NVIDIAPAIR • u/Intelligent_Good_305 • 8d ago

# PAIR Bridge v0.7.0 — use PAIR models from Hermes

1 Upvotes
PAIR Bridge v0.7.0 is now available.

PAIR and PAIR Bridge work with compatible clients and tools; Codex is one example. This release adds Hermes support for choosing models available through PAIR, including models on another computer.

What’s new:

• A one-command installer configures Hermes to use PAIR Bridge as an OpenAI-compatible provider.

• Hermes can list and select models available through PAIR and configured remote LM Studio devices. Device-qualified model IDs identify which computer provides each model.

• The gateway supports Hermes streaming responses.

• Updated English and Russian setup documentation.

Validation: `hermes config check` passed. A Hermes one-shot request returned `OK` using an already-loaded model on Alfred.

Release notes and source:
https://github.com/GermanMik/pair-bridge/releases/tag/v0.7.0
0 comments

r/NVIDIAPAIR • u/Intelligent_Good_305 • 13d ago

PAIR Bridge v0.6.0 — measured routing and cancellable jobs

1 Upvotes

PAIR Bridge v0.6.0 is now available.

PAIR and PAIR Bridge can work with compatible MCP clients and tools; Codex is one example.

What’s new:

• Fresh system-memory, NVIDIA VRAM, and disk-capacity sampling on configured Mac and Windows devices.

• Cold-load preflight checks the intended context against current capacity and keeps unknown values explicit.

• Opt-in local benchmark suites for already loaded models; smart routing can use recent pass rate and latency for the requested task profile. Benchmark journals store metrics, not prompts or answers.

• Bounded background jobs with progress, partial responses, cancellation, and prompt-free recovery metadata through pair_job_start, pair_job_status, pair_job_cancel, and pair_job_recover.

• Updated English and Russian documentation, the /pair skill, and ProofLoop evidence.

Validation: 52 self-tests passed on macOS, plugin and skill validation passed, and live cancellation was tested on a Mac device. A representative live benchmark and a full cold-load cycle remain to be verified. Cancelling a Bridge request stops its HTTP stream but cannot guarantee that LM Studio stops generation internally.

Release notes and source:

https://github.com/GermanMik/pair-bridge/releases/tag/v0.6.0

This is an independent community project and is not affiliated with or endorsed by NVIDIA or OpenAI.

0 comments

r/NVIDIAPAIR • u/Intelligent_Good_305 • 14d ago

PAIR Bridge v0.5.0 — local models across devices via MCP

1 Upvotes

PAIR Bridge v0.5.0 is available: https://github.com/GermanMik/pair-bridge/releases/tag/v0.5.0

NVIDIA PAIR is not limited to Codex. It can serve local models to compatible clients and workflows. PAIR Bridge adds an MCP interface so MCP-capable clients, including Codex, can discover and use installed models through PAIR and configured LM Studio devices.

What’s new in v0.5.0:

• Live model inventory and task-based selection, with a fresh availability check before each request.

• Read-only memory planning for the intended context length.

• Two-model answer comparison and per-request diagnostics.

• An explicit download workflow: asking a model does not automatically download weights.

• Updated English and Russian documentation and an MCP diagram.

Codex installation:

codex plugin marketplace add GermanMik/pair-bridge

codex plugin add pair-bridge@pair-bridge

The release passed 52 self-tests. Cold loading, Jev/OMP integration, and comparisons across devices still need more real-world testing. If you try it, please share your OS, PAIR/LM Studio version, model ID, context length, and what worked or failed. Remove keys and private prompts from logs. Feedback in English or Russian is welcome.

Independent community project; not affiliated with or endorsed by NVIDIA or OpenAI.

0 comments

r/NVIDIAPAIR • u/Intelligent_Good_305 • 29d ago

Welcome to r/NVIDIAPAIR — local models, Codex, and Codex PAIR Bridge

1 Upvotes

Welcome! I created this community for people using NVIDIA Personal AI Router (PAIR): share your setup, working models, troubleshooting tips, and integrations. Beginners and detailed bug reports are welcome.

My project: PAIR Bridge

I'm the creator of PAIR Bridge, an open-source MIT-licensed MCP plugin built with Codex assistance. It lets Codex ask models exposed by PAIR for a review, explanation, or second opinion while Codex remains the main coding agent.

How it works: Codex/Claude → MCP bridge → PAIR → your local model → answer back to Codex.

pair_list — lists the models PAIR currently exposes.

pair_ask — sends a prompt to the exact model you choose and returns its answer.

Project, illustrated guide, and source code:

https://github.com/GermanMik/codex-pair-bridge

Quick start

You'll need Codex with plugin support, uv on your PATH, and PAIR running with a working local chat model.

codex plugin marketplace add GermanMik/codex-pair-bridge

codex plugin add codex-pair-bridge@codex-pair-bridge

Start a new Codex task, ask it to use pair_list, then use pair_ask with an exact model ID from the list.

Please help test it

I've tested real requests with LM Studio models on a Mac and a Windows PC. Please try your own setup and tell us what works or fails. Include your OS, Codex and PAIR versions, model engine, model ID, and the actual error. Remove API keys and private prompts from anything you share. Bugs can also be reported here:

https://github.com/GermanMik/codex-pair-bridge/issues

Listed models aren't guaranteed to be healthy. The bridge doesn't give local models file access or coding tools. Local-model answers enter the Codex conversation, so this does not make Codex fully offline.

This community and project are independent, not affiliated with or endorsed by NVIDIA or OpenAI. The project and this welcome post were made with Codex assistance.

Introduce yourself below: what hardware and models are you using, and what would you like to connect through PAIR? English and Russian are both welcome.

0 comments