Local-First GPU Inference Rig
A self-hosted, high-performance GPU inference rig serving the entire OpenClaw autonomous fleet.
The Problem
Relying entirely on cloud APIs like OpenAI and Anthropic for 24/7 autonomous agents introduces massive continuous costs, rate limits, and data privacy concerns.
The Constraints
We required a self-hosted physical infrastructure capable of running massive parameter LLMs locally at high speed, with zero external dependencies.
Capabilities Utilized
- ▪GPU Infrastructure
- ▪Self-Hosted LLMs
- ▪Hardware Architecture
- ▪Network Engineering
The Approach
We architected and built Monad-1: a dedicated local inference server powered by an NVIDIA RTX PRO 6000 Blackwell GPU and a Threadripper CPU.
The System
Monad-1 is equipped with 96 GiB of VRAM and a Threadripper 9970X processor. It serves as the local LLM backbone for the OpenClaw fleet, providing private, unmetered AI inference.
The Outcome
Eliminated cloud token costs for routine agent operations and unlocked the ability to run uncensored, deeply integrated models locally. It currently publishes live telemetry (token counts, GPU utilization) directly to our dashboards.