With a built-in annual income of 13 million, does Spheron’s "issue coin after revenue targets are met" set a new benchmark for the AI sector?

Another project has launched its TGE with an ARR report! Recently, Spheron Network announced its TGE with over $13 million in ARR revenue.

Revenue is generated, the ecosystem is running, and then we talk about TGE. Will this standard become the norm for TGE in the AI infrastructure track in the future?

Let's take a closer look at the Spheron project:

1. Spheron Network is a decentralized computing network that provides services for high-performance computing tasks such as AI training, inference, and rendering by aggregating global GPU/CPU resources.

In addition to computing power resources, the platform also integrates IPFS storage, ENS domain management, and Arbitrum-based smart contract deployment, providing relatively complete infrastructure support for AI developers.

From a technical architecture perspective, Spheron has built a relatively complete product matrix that covers all aspects from computing power supply to application scenarios.

Fizz Nodes, as the core infrastructure of the entire network, allows individual users—especially gamers—to contribute idle GPUs/CPUs to the network and earn rewards through a simple onboarding process.

This design significantly lowers the threshold for computing power supply, incorporating decentralized personal devices, and quickly forms a decentralized computing power network through a B2C revenue sharing model.

KlippyAI serves as an AI video creation tool directly targeting end-users, with service fees paid in $SPON tokens. It has currently generated nearly 5,000 AI video NFT data on Base L2.

Skynet differs from most Agents by allowing developers to access computing resources and attempting to enable AI Agents to pay for computing power directly with tokens, while also providing a one-click service for everything from wallet creation to contract deployment.

In addition, products such as Supernoderz (Node as a Service), Aquanode (AI Inference Workload), and Spheron Console (One-click GPU Access) together with Fizz Nodes form a complete closed loop from supply to demand.

2. From the operational data, Spheron has demonstrated a certain network scale. 44,000 active nodes distributed across more than 170 countries provide over 8,300 GPUs and more than 600,000 CPUs of computing power, paying out over $500,000 in node rewards each week. In particular, regarding the revenue structure, among the $13M+ ARR, AI business accounts for $7.6 million, indicating that AI applications have indeed generated real paid demand.

However, the sustainability of this bilateral market model essentially depends on whether the supply and demand sides can maintain synchronized growth.

The computing power suppliers receive token rewards, while the demand side pays tokens to use the services, and the platform charges service fees—sounds great, but in actual operation, there are many challenges: Can the service quality of the decentralized network be stable? How long can the cost advantage over giants like AWS and Google Cloud be maintained?

3. The AI Agent infrastructure is indeed a large market that is still in its early stages. Spheron has a certain advantage in the time window by laying out relevant services in advance. However, the competition in this field is much more intense than expected.

Platforms like Hyperbolic, IO.NET, VANA, and Sahara AI have differentiated positioning and are all focusing on AI infrastructure services.

The market pattern is far from being finalized; the eventual winner may not be the one with the most advanced technology, but rather the one that performs the most balanced across comprehensive dimensions such as product iteration speed, ecological construction capability, and service stability.

Anyway, from a broader industry trend perspective, if "entering TGE with ARR" really becomes the new standard for the AI infra track, it may not be a bad thing for the entire industry.

At least it can make the market pay more attention to actual products and revenue, rather than pure concept hype.