OpenGPU

OpenGPU (OGPU) is a global execution and routing layer for AI and high-performance computing (HPC), designed to move workloads across distributed GPU infrastructure in real time.

Instead of acting as a marketplace or a single cloud provider, OpenGPU functions as an orchestration layer above GPU supply. Centralized clouds, independent data centers, and individual GPU operators all become interchangeable execution targets within a single global network.

OpenGPU enables AI inference, training, rendering, and data-intensive workloads to be routed dynamically based on performance, availability, and cost, without vendor lock-in or regional constraints.

Architecture Overview

OpenGPU consists of two complementary execution layers:

1. OpenGPU Mainnet (Blockchain Execution Layer) OpenGPU operates its own purpose-built Layer 1 network, OpenGPU Mainnet, using a Lachesis DAG-based consensus protocol.

Sub-second finality 10,000 transactions per second Fully EVM-compatible Optimized for real-time task coordination and execution tracking

The blockchain is used only where it adds value: task allocation, validation, execution tracking, and settlement. It is not designed for general-purpose DeFi or unrelated smart contracts.

Live network activity is publicly verifiable at: https://ogpuscan.io

2. Relay (Enterprise Routing Layer) Relay is OpenGPU’s Web2-friendly execution gateway that allows enterprises and developers to route AI workloads using familiar cloud-style workflows.

Relay abstracts the underlying blockchain and decentralized infrastructure, enabling enterprises to:

Route workloads without touching crypto directly Pay per task Avoid vendor lock-in Access global GPU capacity on demand

https://relay.opengpu.network

Neo (Autonomous AI Execution on OpenGPU) Neo is OpenGPU’s autonomous AI agent, built as a live example of what the network can power in practice. Rather than being a concept demo, Neo runs on OpenGPU infrastructure and showcases how AI agents can execute real workloads through the network. It represents a practical layer on top of OpenGPU’s routing and execution stack, demonstrating how autonomous systems can be deployed without relying on traditional centralized cloud dependency. Neo helps illustrate OpenGPU’s broader vision: not just routing compute, but powering the next generation of AI-native applications and agents that require scalable, flexible, and globally available execution.

How OpenGPU Is Used Clients submit compute workloads (inference, training, rendering, etc.) OpenGPU routes tasks dynamically across available GPU capacity Providers execute workloads and earn rewards Completion and validation are recorded on OpenGPU Mainnet

Anyone can participate: Enterprises and developers can run workloads

Data centers and individual GPU operators can contribute capacity and earn income

Token Utility (OGPU) The OGPU token is used for:

Task execution settlement Network coordination Provider incentives Economic security of the routing layer

All tokens are already in circulation. There are no unlock schedules.

What OpenGPU Is Not Not a GPU marketplace Not a single cloud provider Not a speculative infrastructure concept OpenGPU is a live, operational execution network.

Mission OpenGPU’s mission is to become the default global routing layer for AI and HPC compute, where workloads move freely across GPU infrastructure as demand scales.

Instead of compute being locked inside silos, OpenGPU enables compute to flow globally.