@Pyth Network How to capture a $50 billion data market with a "dual-track system"? When it comes to market data services, many people's first reaction is "high barriers, high fees," but @Pythnetwork has taken a different path — first opening up the ecosystem with free data, then locking in institutions with paid subscriptions. This "dual-track" strategy is at the core of its approach to entering the $50 billion cross-sector data industry. First, let's look at the free end, the "inclusive model": currently, @Pythnetwork has opened over 400 free data sources covering all categories including cryptocurrencies, stocks, and commodities. It supports major public chains like Solana and Ethereum and provides zero-barrier access tools for Web3 developers. Recently, it added 12 high-frequency data sources for the Sui ecosystem, from BTC/USDT to AAPL stock prices, allowing developers to access millisecond-level data without fees. This idea of "let the ecosystem run first" has attracted over 200 projects, supporting a total value locked (TVL) of $4.4 billion in the DeFi sector, laying a solid foundation for subsequent commercialization. Now, let's look at the paid end, the "institutional model": with the launch of the second phase subscription products, @Pythnetwork has begun to release core value to traditional financial institutions. Unlike the "one-size-fits-all" pricing of ordinary data service providers, its subscription services are customized based on institutional needs — for example, providing exclusive multi-chain data APIs for quantitative funds and real-time delivery data for commodity traders, and even on-chain data verification services. More critically, behind these services is the support from over 100 top data sources, from market maker Jane Street to exchange Binance, with each piece of data having been verified firsthand. This is why more and more traditional institutions are willing to pay for it. The token is the key connecting the free ecosystem and paid services. On the free side, developers can earn token rewards by using data and participating in ecosystem building; on the paid side, part of the fees paid by institutions for subscription services flows into the treasury and is then distributed through PYTH — this "use benefits, pay dividends" model allows both individual developers and large institutions to deeply bind with the ecosystem. As the second phase progresses, $PYTH application scenarios will also extend to data quality voting, DAO governance, and other fields, truly realizing "tokens as data ecosystem passports." From empowering small projects for free to providing paid services for large institutions, @Pythnetwork is breaking down the barriers of data services with a "two-legged" approach. Do you think this "free first, then paid" model will become the mainstream play in the future market data industry? Feel free to share your views in the comments! #PythRoadmap $PYTH
