Cluster-scale AI processing engine for local inference on commodity hardware.
Cluster-scale AI processing engine for local inference on commodity hardware.
Run massive mixture-of-experts models with hardware-adaptive local execution.
A revolutionary AI processing engine that brings cluster-scale power to desktop computers. Run massive mixture-of-experts models (100B-1T parameters) on modest hardware by dynamically loading only the required expert networks as needed.
Intelligently loads only required expert networks on-demand
Leverages high-speed storage for rapid parameter streaming
GPU + CPU/RAM + SSD hierarchy for optimal performance
Automatically adapts to available hardware resources
Fine-tuned for fast prompt processing and generation
Run massive MOE models on your own hardware. Perfect for developers, researchers, and organizations building AI applications with local inference.
Understanding how monaddLLM enables cluster-scale AI inference on desktop hardware.
Modern frontier AI models utilize MOE architecture with thousands of specialized expert networks. During inference, only a small subset of experts are activated per token, creating natural sparsity.
monaddLLM implements intelligent expert offloading, loading only required expert networks on-demand from high-speed storage, reducing GPU memory requirements.
A three-tier cache hierarchy (GPU, CPU/RAM, SSD) optimizes expert retrieval with hot experts in fast memory and cold experts on high-speed storage.
The engine adapts to available hardware resources and scales cache/offloading strategies to maintain inference quality and speed.
From independent professionals to regulated enterprises.
For professionals and power users
For small, collaborative teams
For individuals and power users
For regulated SMEs, annual contract