> ## Documentation Index
> Fetch the complete documentation index at: https://wp.farlabs.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# System Requirements

FAR AI is designed to run on widely available consumer and prosumer GPU hardware. The following table summarizes the minimum and recommended specifications for a node.

| **Component**    | **Minimum**                                        | **Recommended**                                                   |
| ---------------- | -------------------------------------------------- | ----------------------------------------------------------------- |
| GPU              | NVIDIA, 10 GB VRAM, <br />RTX 30 series or newer   | RTX 3080 / 3090 / 4090 or <br />equivalent, 16–24 GB VRAM         |
| System RAM       | 16 GB                                              | 32 GB or more                                                     |
| Storage          | 100 GB free for model <br />cache, SATA SSD        | 500 GB or more, NVMe <br />SSD strongly preferred                 |
| Internet         | 100 Mbps for initial setup; <br />2–3 Mbps ongoing | 200 Mbps or more; under <br />50 ms latency to <br />orchestrator |
| Power Supply     | 150 W headroom above <br />GPU rated power         | Stable supply with UPS <br />protection recommended               |
| Operating System | Windows 10 (build 19041+) <br />or Windows 11      | Windows 11, latest updates <br />applied                          |

VRAM is the most important factor for earning potential. More VRAM allows a node to serve larger, more valuable models. NVIDIA drivers must be installed before running the FAR AI installer, the installer handles all other software dependencies automatically.

Storage speed has a meaningful impact on job start latency. A large model loads significantly faster from a high-speed NVMe drive than from a standard SATA SSD, and faster load times mean higher effective availability and more earning opportunities. The installer automatically selects the best available drive for model caching.