Base's POD Token Surges 14x in May with Unique Buyback Model

$POD: The Buyback Engine Powering the Dolphin Inference Network

Source: Dolphin

Original compilation: Yuliya, PANews

Editor’s Note: Recently, the AI narrative within the Base ecosystem has experienced explosive growth, with privacy-first generative AI platform Venice ($VVV) and its ecosystem projects standing out most prominently. As a co-developer of Venice’s core default model, the Dolphin network and its token $POD delivered an extraordinary performance in May, with its market cap surging from $12.2 million to $192 million—an increase of over 14x. This article provides a detailed breakdown of Dolphin Network’s unique “peer-to-pool” economic model, its token value capture mechanism, and its innovative design for securing network security through staking and slashing. Below is a comprehensive analysis of these mechanisms:

The Dolphin network is designed as a peer-to-pool system to repurpose idle GPUs. Each AI model runs on a GPU provided by the network.

This differs from most AI DePIN projects. In other networks, buyers typically 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” that collectively processes task requests from users. The system randomly assigns tasks based on node availability, with no direct connection between those submitting requests and those providing nodes. Nodes earn rewards solely based on the number of AI computation tasks they complete (i.e., inference tokens), with rewards paid in POD tokens issued by the protocol treasury.

On the demand side, API users directly purchase quotas 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 is used to repurchase POD tokens on the market—directly offsetting token inflation.

Buyers and sellers are separated, which means the POD rewards sent to nodes can be more or less than the POD we earn from revenue.

For a more intuitive illustration, let’s examine a specific case of running the Qwen3.6-35B model on the Dolphin network:

· Current cost to run datagen.dphn.ai: $0.50 per 1 million tokens processed.

· The cheapest comparable competitor on OpenRouter: $1.00 per 1 million tokens.

· Dolphin's fee to users: $0.70.

· Dolphin's fee paid to the node: $0.50.

· Net repurchase funds: $0.20 is generated for every 1 million tokens created.

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

This model is considered a highly promising application direction in the DePIN space, primarily due to the following reasons:

· Extremely high AI inference demand: Market demand for AI inference computing power is currently experiencing explosive growth.

· Vast pool of idle computing power: There is an enormous supply of idle gaming GPUs capable of running local AI models. This network model feels similar to traditional GPU mining (PoW), but with far greater earning potential, as it generates truly commercially valuable AI computations.

· Geographic Independence: Unlike many DePIN networks, the geographic location of AI inference is not critical, thereby avoiding coverage issues. Due to the high geographic flexibility of AI inference, latency of a few hundred milliseconds has minimal impact on user experience, enabling the Dolphin network to connect consumers and computing resources globally, significantly enhancing the scalability and utilization of each node.

· The Necessity of Liquidity Pooling: This is the only way to unlock the largest group of GPU suppliers—gamers and PC enthusiasts. It allows nodes to come online or go offline at any time, without requiring fixed uptime as in P2P node rental models. Previous GPU DePIN projects required a one-to-one binding between consumers and nodes, which is impractical for idle GPUs such as those in gaming PCs or data center graphics cards, since owners may wish to reclaim their machines at any moment. After all, no one wants to rent a virtual machine that could suddenly go offline if the owner decides to use their GPU again.

POD is the only valuable asset within the Dolphin ecosystem. All revenue generated by the network is 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 POD holders, staking tokens in the xPOD vault unlocks multiple exclusive benefits:

Earn direct, automatic compounding dividends from network token buybacks.

· Receive daily AI inference credits to freely use all models available online.

· Enjoy premium subscription status in Dolphin’s web chat room, bots, and other ecosystem applications.

In its tokenomics design, Dolphin draws on the best practices from numerous successful DeFi projects and deeply integrates the most relevant components for a decentralized AI inference and training network:

Adopting the ETH mechanism: Node operators and validators must post a deposit, which will be directly slashed if malicious behavior occurs.

· Adopt the CRV mechanism: Provide a reward acceleration feature for node operators. Locking POD can boost rewards by up to 2x, and based on deposit-to-reward ratios on other platforms, a multiplier of 1.5x to 2x is highly competitive in the market.

· Adopt the xSUSHI/yCRV mechanism: Introduce an auto-compounding staking vault. Users do not need to manually claim rewards, allowing xPOD (the staked version of the Dolphin token) to be directly used as collateral by node operators.

· Inspired by the stAAVE mechanism: Implemented a reasonable withdrawal cooldown period and withdrawal time window to ensure network fund stability.

· Adopt the vlCVX/veCRV mechanism: A "bribery market" has been established for daily unused xPOD computation quotas, allowing users to sell excess quotas and earn higher staking rewards.

In a decentralized computing network, cheating is undoubtedly the greatest threat. If left unchecked, node operators might secretly replace the AI models with smaller, stripped-down, or even fake ones while still claiming rewards. This would cause output quality to collapse, driving away those who purchase computing power and preventing the entire ecosystem’s flywheel from ever getting started.

To address this challenge, the Dolphin network introduces a "deductible deposit" mechanism, deeply aligning the node operators' incentives with the value of the POD token. If malicious cheating is confirmed, the node will have a deposit equivalent to four weeks of income deducted, making cheating economically unviable.

By default, node operators earn PODs in a "bonded" state. Once a node accumulates an amount of bonded PODs equivalent to four weeks' earnings, they can choose, at each weekly settlement, to continue receiving bonded PODs or to receive liquid PODs that can be traded at any time.

If you choose to claim liquid POD, the system will deduct a 20% fee, which will be directly deposited into the xPOD staking vault to be distributed among other stakers and node operators who have securely bonded their deposits.

Nodes can further stake xPOD into the bonding contract, which not only increases their earnings but also qualifies them to become validators on the network.

The POD reward multiplier determines how much extra a node can earn on top of its base reward. This mechanism is inspired by Curve Finance’s liquidity provider (LP) acceleration system, but Dolphin has specifically adapted it for a decentralized AI network, incorporating features such as usage-based rewards, unified deposit calculations across all accounts, and penalties for violations.

In simple terms:

Nodes earn base rewards by completing AI computations, verifying work, and performing related protocol tasks.

The system will multiply your node rewards by a multiplier based on the number of tokens linked to your account and your yield rate.

When calculating the yield ratio, the system considers your average base rewards over the past few weeks, using a "rise fast, fall slow" smoothing algorithm: when you take on more computational tasks, your average yield metric rises quickly; however, when you become inactive, it declines slowly.

· If your account has maintained a deposit with over three months of rewards and has at least 50,000 POD in active deposit, you are eligible to become a validator.

· If your bonded deposit is equivalent to six months (26 weeks) of your earnings, the system guarantees that your rewards will be multiplied by at least 1.5 times.

If your bonded deposit exceeds six months' earnings, your reward multiplier can reach up to 2x. The exact multiplier depends on your relative proportion compared to other users with excess bonding, as well as the absolute amount by which you exceed the six-month target.

All calculations are based solely on the number of PODs; the reward system does not involve any fiat price oracles. Deposits are calculated per account (wallet), and the resulting reward multiplier applies to all nodes under your account. If you add more nodes, your total account earnings will increase, so you must proportionally increase your active deposit to maintain the original reward multiplier.

Finally, the Dolphin network will release the paper "Encrypted Live-Weight Proofs for Decentralized Inference" tomorrow. The paper will detail a lightweight verification system capable of confirming whether nodes are running the correct model on various hardware, going beyond standard TEE verification that only works on enterprise NVIDIA GPUs.

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