Author: Dolphin

Translation: Yuliya, PANews

Editor's Note: Recently, the AI narrative of the Base ecosystem has experienced explosive growth, notably with the privacy-focused generative AI platform Venice ($VVV) and its ecological projects. (Related Reading:The "VVV" concept that has increased ninefold in six months, the new main line of AI in the Base ecosystem) As a co-developer of Venice's core default model, Dolphin Network and its token $POD performed astonishingly in May, with its market cap skyrocketing from $12.2 million to $192 million, an increase of over 14 times. This article elaborates on Dolphin Network's unique "Peer-to-Pool" economic model, the token value capture mechanism, and the innovative design to ensure network security through staking and penalty mechanisms. Below is a detailed breakdown and analysis of the mechanisms:

Peer-to-Pool Economic Model Design

Dolphin Network is designed as a "Peer-to-Pool" system, aimed at recycling everyone’s idle GPUs. Each AI model runs on a GPU provided by the network.

This is different from most AI DePIN systems. In other networks, buyers usually rent a node directly from the provider, establishing a one-to-one "session".

• On the supply side, nodes running the same model form a "pool" to collectively process the task requests submitted. The system randomly assigns tasks based on the availability of nodes, and there is no direct contact between the requestor and the provider. The only criterion for nodes to earn rewards is how many AI computation tasks they handle (i.e., inference tokens), with rewards paid in POD tokens from the protocol treasury.

• On the demand side, users using the API purchase quotas directly from the protocol. Dolphin Network accepts various cryptocurrencies as payment, including $POD, $ETH, $BTC, $USDC, $XMR, and $ZEC.

100% of all income received by the protocol will be used to repurchase POD tokens in the market—this directly offsets the issuance of new tokens.

Buyers and sellers are separate, meaning the POD rewards sent to nodes can be more or less than the POD we earn from the income.

To illustrate more intuitively, let’s look at a specific case of running the Qwen3.6-35B model on Dolphin Network:

• Current cost of running datagen.dphn.ai: $0.50 for processing 1 million tokens.

• Cheapest similar competitor price on OpenRouter: $1.00 for 1 million tokens.

• Fees charged to users by Dolphin: $0.70.

• Fees paid to nodes by Dolphin: $0.50.

• Net buyback funds: $0.20 generated for every 1 million tokens.

In other words, Dolphin Network’s pricing is not only 30% lower than the cheapest centralized provider, but also generates a pure profit of $0.20 for every 1 million tokens, which can be used to buy POD in the market.

Why is this the best application scenario for DePIN?

This model is seen as a highly promising application direction in the field of DePIN, based on the following reasons:

• Extremely high demand for AI inference: The market's thirst for AI inference computing power is at an explosive stage.

• Massive idle computing power pool: The supply of idle gaming GPUs capable of running local AI models is immense. This network model feels reminiscent of previous GPU mining (PoW), but since it produces AI computations with real commercial value, the potential for profit is much greater.

• Ignoring geographical location restrictions: Unlike many DePIN networks, the geographic location of AI inference is not important, thus avoiding coverage issues. The geographical flexibility of AI inference means that a few hundred milliseconds of latency has very little impact on user experience, enabling Dolphin Network to connect global consumers and computation resources, greatly enhancing the scalability and utilization of each node.

• The necessity of liquidity pooled computing: This is the only way to unlock the largest GPU supply group (gamers and computer enthusiasts). It allows nodes to go online or offline at any time, without needing to guarantee a fixed online time as in P2P node rentals. Previous GPU DePIN projects required a one-to-one binding between consumers and nodes, which is impractical for idle GPUs like gaming PCs or data center graphics cards since the owner may want to take the computer back for personal use at any moment. After all, no one wants to rent a GPU and then suddenly lose connection when the owner takes it back.

Token Mechanism and Value Accumulation

POD is the only valuable asset in the Dolphin ecosystem. 100% of all revenue generated by the network will automatically be used to repurchase POD in the market. Furthermore, Dolphin has no external equity structure based on shareholders, nor will it ever introduce one in the future.

For holders of POD, staking tokens in the xPOD treasury grants multiple exclusive privileges:

• Receive direct automatic compound dividends from network token repurchases.

• Obtain daily AI inference quotas, allowing free use of all models on the network.

• Enjoy a premium subscription status in Dolphin’s web chat room, bots, and other ecological applications.

In designing the token economics, Dolphin draws from numerous excellent DeFi projects and deeply integrates the aspects that best fit a distributed AI inference and training network:

• Referencing the ETH mechanism: Node operators and validators are required to pay a deposit, which will be deducted (forfeited) if malicious behavior occurs.

• Referencing the CRV mechanism: Provides rewards acceleration function for node operators. Locking POD can double the rewards, whereas other platforms' deposit yield ratios show that a multiplier of 1.5 to 2 times is very competitive in the market.

• Referencing xSUSHI/yCRV mechanism: Introduces an automated compound staking treasury. Users do not need to manually claim rewards, meaning xPOD (the staked state of Dolphin tokens) can be directly used as collateral for node operators’ deposits.

• Referencing stAAVE mechanism: Sets reasonable withdrawal cooling periods and withdrawal time windows to ensure the stability of network funds.

• Referencing vlCVX/veCRV mechanism: Establishes a "bribery market" for daily unused xPOD quota calculations. Users can sell unused computing quotas to earn higher staking returns.

Deposit Binding, Violation Penalties, and Reward Doubling Mechanism

In decentralized computing networks, cheating is undoubtedly the biggest threat. If unchecked, node operators might secretly switch to using smaller, stripped-down, or completely fake AI models and still earn rewards. Consequently, output quality could collapse, those buying computing power might flee, and the entire ecosystem's flywheel may never start turning.

To tackle this challenge, Dolphin Network has introduced a "deductible deposit" mechanism that deeply binds the interests of node operators with the value of POD tokens. If malicious cheating behavior is confirmed, the node will directly lose a deposit equivalent to four weeks' income. This makes cheating economically unfeasible.

By default, node operators earn POD that is in a "bound state". When a node accumulates enough bound POD equivalent to four weeks of income, they can choose during the weekly settlement whether to continue receiving the bound POD or to receive liquid POD that can be traded at any time.

If they choose to receive liquid POD, the system will deduct a 20% fee. This money will go directly into the xPOD staking treasury, distributed to other stakers and node operators who have honestly bound their deposits.

Nodes can also further deposit xPOD into the binding contract, which not only increases their returns but also grants them the qualification to validate other nodes in the network.

The POD reward multiplier determines how much additional money a node can earn beyond the basic rewards. This mechanism is inspired by the liquidity provider (LP) acceleration mechanism of Curve Finance, but Dolphin has made specific modifications for decentralized AI networks, adding features such as usage-based reward distribution, unified account-wide deposit calculations, and violation penalties.

In simple terms:

• Nodes earn basic rewards by completing AI computations, validation work, and related protocol tasks

• The system will multiply your earned node rewards by a factor based on the amount of tokens bound in your account and your yield ratio

• When calculating yield ratios, the system will consider the average of your basic rewards over the past few weeks and employs a "fast to rise, slow to fall" smoothing algorithm: as you take on more computing tasks, your average yield metric rises quickly; but when you have downtime, it falls slowly

• If your account maintains deposits related to earnings for over three months and at least 50,000 POD as active deposits, you qualify to become a validator

• If your bound deposits are equal to six months (26 weeks) of earnings, the system guarantees your rewards will at least be multiplied by 1.5 times

• If your bound deposits exceed six months of earnings, your reward multiplier can reach up to 2 times. How much it can reach depends on your ratio to other excess bound depositors and the absolute quantity of your excess over the six-month target

All calculations are based solely on the quantity of POD, and the reward system does not involve any fiat currency price oracles. Deposits are calculated per account (wallet), and the calculated reward multipliers apply to all nodes under your account. If you add more nodes, your total account earnings will increase, so you need to proportionately increase active deposits to maintain the original earnings multiplier.

Finally, Dolphin Network will release a paper titled "Encrypted Live-Weight Proofs for Decentralized Inference" tomorrow. This paper will detail a lightweight verification system capable of verifying whether nodes running the correct model on various hardware, surpassing the standard TEE verification that can only be used on enterprise NVIDIA graphics cards.

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