If you've been in the crypto space for a long time, you know that many projects only boast about their 'narrative stories' without having a legitimate way to make money. But Pyth Network is different; it has laid out a viable revenue model and tightly binds the PYTH token to real cash flow—this is the highlight to watch!

Let's talk about its most stable core revenue: data access fees. Pyth has created a 'Pull model', which means simply 'pay as you go': developers or protocols only pay when they need data, unlike the old 'Push model' where data was continuously updated regardless of usage, wasting costs. This approach is very clever, reducing protocol costs, and users only spend what they need. As more projects are integrated, the demand for data requests can explode, and this part of the revenue will naturally increase.

What's even more amazing is that it also engages in 'side businesses' to earn additional value. In addition to providing market data for DeFi, Pyth's Entropy random number service has long been up and running—handling 2.89 million requests in the second quarter of 2025, whether for random item drops in blockchain games, fair distribution of NFTs, or lottery draws to prevent MEV, it is all applicable. In the future, expanding to MEV prevention tools, clearing and settlement data businesses, this part of 'non-market income' can become more solid, and the income structure will stabilize significantly.

The real ace up the sleeve is targeting the institutional market. Pyth is now focusing on promoting institutional subscription services, and the logic is quite simple: financial institutions and regulators can pay to obtain customized off-chain data, such as stock and ETF prices, or even macro indicators like GDP, with payment options in USD, stablecoins, or PYTH. It is worth noting that the global financial data market is valued at $44.3 billion; even if Pyth only captures 1%, it could earn $440 million a year—this is much more appealing than competing within the crypto circle!

The key point is that how the earned money is used is entirely decided by the DAO. The treasury can buy back and burn PYTH, directly enhancing the token's scarcity; it can also reward market makers who provide quality data, making the data quality more reliable; or even distribute dividends to token holders. This way, PYTH is not simply a 'speculative token' anymore; it has become a 'quasi-equity asset' with governance rights and cash flow distribution, firmly anchored in value.

Doing the math reveals the potential: Currently, Pyth supports a TVS of $5.31 billion, with millions of data calls daily. Even if each call only charges $0.001 to $0.01, the market data alone could earn tens of millions of dollars a year. Coupled with institutional subscriptions and value-added services, an annual revenue of over $100 million is entirely possible, and every penny's destination is publicly and transparently managed by the DAO, with no tricks involved.

Ultimately, Pyth's monetization logic is a three-layer closed loop: first relying on DeFi usage fees as a base, then filling gaps with value-added services, and finally scaling up through institutional subscriptions, and returning funds to PYTH holders through the DAO. It is far from a simple oracle; it is clearly a decentralized prototype of Bloomberg! Once the first institutional subscription fee arrives, the valuation logic of PYTH will need to be completely rewritten—at this stage, it’s definitely worth taking a good look at its layout.

@Pyth Network #PythRoadmapand $PYTH