Original Title: $POD: The Buyback Engine Powering the Dolphin Inference Network
Original Source: Dolphin
Original Compilation: Yuliya, PANews
Editor's Note: Recently, the AI mainline narrative of the Base ecosystem has experienced explosive growth, with the privacy-focused generative AI platform Venice ($VVV) and its ecological projects being the most notable. As a co-developer of Venice's core default model, the Dolphin network and its token $POD performed astonishingly in May, with its market capitalization soaring from $12.2 million to $192 million, an increase of over 14 times. This article elaborates on the Dolphin network's unique "Peer-to-Pool" economic model, the token value capture mechanism, and the innovative design that ensures network security through staking and penalty mechanisms. Below is a detailed breakdown and analysis of the mechanisms:
Peer-to-Pool Economic Model Design
The Dolphin network is designed as a "Peer-to-Pool" system, aiming to repurpose idle GPUs from users. Each AI model runs on a GPU provided by the network.
This differs from most AI DePINs. In other networks, buyers typically rent a node directly from providers, establishing a one-on-one "session."
· On the supply side, nodes running the same model form a "pool" that together processes the task requests sent by users. The system randomly assigns tasks based on the availability of nodes, and there is no direct connection between the requester and the provider. The only criterion for nodes to earn rewards is how many AI computation tasks (i.e., inference tokens) they process, with rewards paid in POD tokens issued by the protocol treasury.
· On the demand side, users of the API purchase credits directly from the protocol. The Dolphin network accepts multiple cryptocurrencies for payment, including $POD, $ETH, $BTC, $USDC, $XMR, and $ZEC.
100% of all revenue received by the protocol will be used to buy back POD tokens on the market—this directly offsets the issuance of new tokens.
Buyers and sellers are separated, meaning that the POD rewards sent to nodes can be more or less than the POD earned from revenues.
To illustrate this more intuitively, we can look at a specific example of running the Qwen3.6-35B model on the Dolphin network:
· The current cost of running datagen.dphn.ai: $0.50 for processing 1 million tokens.
· The cheapest comparable product on OpenRouter: $1.00 for 1 million tokens.
· The fee charged to users by Dolphin: $0.70.
· The fee paid to nodes by Dolphin: $0.50.
· Net buyback funds: $0.20 generated for every 1 million tokens.
In other words, the pricing of the Dolphin network is not only 30% lower than the cheapest centralized provider, but also allows for a pure profit of $0.20 from every 1 million tokens generated to buy POD on the market.
Why is this the Best Application Scenario for DePIN?
This model is seen as a highly promising application direction in the DePIN field, mainly for the following reasons:
· Extremely high demand for AI inference: The market's desire for AI inference computing power is in an explosive phase.
· A large pool of idle computing power: There is an immense supply of idle gaming GPUs capable of running local AI models. This network model feels similar to previous GPU mining (PoW), but because the output is genuinely commercially valuable AI computation, the potential for profit is much greater.
· Ignoring geographical restrictions: Unlike many DePIN networks, the geographical location of AI inference is not important, thus avoiding coverage issues. Due to the high flexibility in geographical location for AI inference, latency of a few hundred milliseconds has little impact on user experience, allowing the Dolphin network to connect consumers and computing resources globally, greatly enhancing the scalability and utilization of each node.
· The inevitability of liquidity pool computing: This is the only way to unlock the largest supply group of GPUs (gamers and PC enthusiasts). It allows nodes to come online or go offline at any time, without needing to ensure a fixed online time like P2P rented nodes. Previous GPU DePIN projects required one-to-one binding between consumers and nodes, which simply does not work for idle GPUs like gaming PCs or data center graphics cards, as the owner may want to utilize their computer at any time. After all, no one wants to rent a GPU only to have the owner suddenly reclaim it, cutting off the virtual machine.
Token Mechanism and Value Accumulation
POD is the only valuable asset in the Dolphin ecosystem. 100% of the revenue generated by the network will be automatically used to repurchase POD on the market. Additionally, Dolphin has no external equity structure based on shareholders and will never introduce one in the future.
For holders of POD, staking tokens in the xPOD treasury provides multiple exclusive benefits:
· Automatic compounding dividends from the network's token buybacks.
· Daily access to AI inference credits, allowing free use of all models in the network.
· Premium subscription status in Dolphin's web chatrooms, bots, and other ecological applications.
In the design of the token economics, Dolphin has drawn on the essence of many excellent DeFi projects and deeply integrated the parts that fit distributed AI inference and training networks:
· Inspired by ETH mechanism: Node operators and validators need to pay a deposit, which will be deducted (forfeited) in case of malicious behavior.
· Inspired by CRV mechanism: Rewards acceleration features are provided for node operators. Locking POD can double the earnings, and based on deposit yield ratios from other platforms, a 1.5 to 2 times acceleration ratio is highly competitive in the market.
· Inspired by xSUSHI/yCRV mechanism: Introducing an automated compounding staking treasury. Users do not need to manually claim rewards, meaning that xPOD (the staked state of Dolphin tokens) can be directly used as collateral for node operators.
· Inspired by stAAVE mechanism: Setting reasonable withdrawal cooling periods and withdrawal time windows to ensure the stability of network funds.
· Inspired by vlCVX/veCRV mechanism: A "bribery market" is established for the calculation of daily unused xPOD credits. Users can sell unused computing credits to earn higher staking rewards.
Deposit Binding, Violation Fines, and Reward Doubling Mechanisms
In decentralized computing networks, cheating is undoubtedly the greatest threat faced. If neglected, node operators may secretly switch to smaller, trimmed, or even fake AI models and still receive rewards. This results in an explosion in output quality, causing buyers of computing power to flee, and the entire ecosystem's flywheel will never spin up.
To address this challenge, the Dolphin network has introduced a "deductible deposit" mechanism that deeply ties the interests of node operators to the value of POD tokens. If malicious cheating is confirmed, the node will be directly deducted an amount equal to 4 weeks' income in deposits. This makes cheating financially unviable.
By default, the POD earned by node operators is in a "bound state." When a node accumulates an amount of bound POD equivalent to 4 weeks’ income, they can choose to receive either the bound POD or the liquid POD that can be traded at any time during the weekly settlement.
If they choose to receive liquid POD, the system will deduct a 20% handling fee. This money will go directly into the xPOD staking treasury, benefiting other stakers and those node operators who honestly bind their deposits.
Nodes can also further deposit xPOD into the binding contract, which not only enhances their earnings but also qualifies them to verify other nodes in the network.
The POD rewards multiplier determines how much extra a node can earn beyond the base 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 rewards, unified account deposit calculations, and violation penalties.
In simple terms:
· Nodes earn base rewards by completing AI computations, verification tasks, and related protocol tasks.
· The system multiplies the node rewards earned based on the number of bound tokens in your account and your revenue ratio.
· When calculating the revenue ratio, the system looks at the average value of your base rewards over the past few weeks, using a "fast-up, slow-down" smoothing algorithm: when you take on more computing tasks, your average revenue metric rises quickly; but when you are idle, it decreases very slowly.
· If your account maintains deposits that exceed 3 months of earnings and your active deposits are at least 50,000 POD, you qualify to become a validator.
· If the deposits you have bound are equivalent to 6 months (26 weeks) of earnings, the system guarantees that your rewards can be multiplied by at least 1.5 times.
· If your bound deposits exceed 6 months of earnings, your reward multiplier can reach up to 2 times. The specific amount will depend on your relative ratio to other excess binders and the absolute amount exceeding the 6-month target.
All calculations are based solely on the number of POD tokens, and the rewards system does not involve any fiat currency price oracle. Deposits are calculated per account (wallet), and the calculated reward multiplier applies to all nodes under your account. If you add more nodes, your total account earnings will increase, so you need to proportionally increase active deposits to maintain the original earnings multiplier.
Finally, the 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 are running the correct models across various hardware, surpassing the standard TEE verification that can only be used on enterprise Nvidia graphics cards.
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