TL;DR
- Pyth ended Q3 with $11.49 million in active ARR, up 86.5% quarter over quarter after adding $5.33 million in net new ARR.
- Pyth-powered venues accounted for 94.1% of $2.09 trillion in Q3 real-world-asset perpetual volume, while prediction markets also expanded usage.
- The network is extending into AI and institutional distribution through Exa integration testing and Nasdaq Basic availability on its Data Marketplace, alongside 276 paying accounts overall at quarter end.
Pyth Network ended the third quarter with $11.49 million in active annual recurring revenue, up 86.5% quarter over quarter as its commercial model expanded beyond onchain price feeds. In its October 8 update, Pyth said it added $5.33 million in net new ARR during Q3 and reached 276 paying accounts. Pyth Pro generated $9.68 million in live ARR, while Pyth Indices contributed $1.81 million across 16 live clients. The Pyth Terminal also added $500,000 in new September ARR. The figures show Pyth developing a market-data business across exchanges, prediction markets and AI applications.
Pyth Expands Across Exchanges, Prediction Markets and AI
Pyth’s exchange footprint grew alongside real-world-asset perpetual markets, which generated $2.09 trillion in Q3 volume. According to Pyth, venues using its data accounted for 94.1% of that activity. Coinbase uses Pyth data for continuously priced thematic markets, while MarketVector indexes calculated with Pyth data underpin equity index futures listed by Coinbase Derivatives. Trade[XYZ], OKX and Lighter use Pyth Pro or Indices for their markets. The expansion builds on Pyth’s earlier commercial growth, showing how institutional market-data infrastructure is becoming embedded in products designed for continuous trading across asset classes.
Prediction markets form another growth vertical. Kalshi uses Pyth prices for stock and commodity markets and named Pyth as the sole Source Agency in September filings for gold and silver perpetuals on its CFTC-registered exchange. Pyth also supplies data to Polymarket’s real-world-asset markets. The company argues that reliable continuous data becomes increasingly important as prediction markets expand from elections and news events into financial assets, commodities and macroeconomic outcomes. This positioning extends Pyth’s role from a crypto oracle toward a cross-asset data layer serving markets that require programmable pricing and settlement inputs.
AI represents the third area Pyth is testing for future commercial deployment. Pyth and Exa are experimenting with a market-data stack for financial agents, combining Exa’s web-scale research context with Pyth’s prices, historical observations and candlestick data through MCP. Pyth also became an approved external distributor of Nasdaq Basic through its Data Marketplace, although clients must license the product directly from Nasdaq and receive prior written approval. Meanwhile, the PYTH DAO approved the 100% Rule, directing every dollar it receives from Pyth products toward open-market PYTH purchases. Pyth’s next phase centers on converting trials, expanding institutional market-data adoption and deepening integrations during Q4 execution.
