> ## Documentation Index > Fetch the complete documentation index at: https://docs.gamerhash.com/llms.txt > Use this file to discover all available pages before exploring further. # Network stats > Live state of the GamerHash AI distributed compute network — devices, GPUs, VRAM, CPU cores, RAM, and storage. The GamerHash AI network is built from contributors' machines, and you can watch its capacity in real time. The public dashboard at [gamerhash.com/en/stats](https://gamerhash.com/en/stats) shows what's connected to the network right now. ## What's tracked | Metric | What it measures | | ------------- | -------------------------------------------------------------- | | **Devices** | Total machines connected to the network and running the AI App | | **GPUs** | Aggregate count of GPUs contributed across all devices | | **GPU VRAM** | Total video memory available for AI inference workloads | | **CPUs** | Aggregate CPU count across the network | | **CPU cores** | Total cores available for CPU-side workloads | | **RAM** | Total system memory across all connected machines | | **Storage** | Total disk capacity contributed by the network | Each metric is shown for two windows: * **Last 24h** — what was active in the past day * **Overall** — cumulative state of the network ## Why this matters For **contributors**, the dashboard gives a feel for how big the network is and how busy it tends to be — a larger network means more workloads in the queue to route. For **AI builders and partners**, it's an at-a-glance view of available compute capacity before integrating with the platform. The numbers are pulled live, so don't expect them to match a snapshot you saw an hour ago. Treat them as a directional read, not a service-level commitment — the queue and machine mix move minute to minute. ## Open the dashboard Real-time numbers from the public dashboard — devices, GPUs, VRAM, CPU, RAM, storage. What it takes to add your GPU to the network.