2. Introduction

Historical scenario; not a current rate card. This comparison uses old assumptions such as $0.005/node-hour, modeled node performance and (in some chapters) fixed burns or token-price projections. The native public mainnet is not yet active. These are not verified current payouts, price forecasts or like-for-like benchmarks; see Pricing Methodology and Status.

Modern AI and machine learning applications require enormous amounts of compute power. Traditional centralized data centers using high–end chips (like Nvidia H100s) demand huge CAPEX and OPEX. These systems often cost billions of dollars in capital investment and incur ongoing expenses for electricity, cooling, network bandwidth, and storage.

In contrast, the GNUS.ai network is built on a decentralized model where:

• End users operate nodes using their own devices.

• The network distributes payouts in GNUS tokens at a nominal rate of $0.005 per hour.

• A deflationary mechanism (token burning) and commission structure increase the token’s value over time.

This report is designed to explain these differences in simple terms and show how node operators benefit from participating in the GNUS.ai network.