io.net has launched a new token burn mechanism directly linked to network revenue. Under the plan, up to 12 million IO tokens could be removed from circulation over the next year. The first burn was scheduled for June 11, coinciding with the network's third anniversary. Future burns will be funded by revenue from customer usage, not new token issuance.
Revenue-Linked Token Burn
io.net calls the system the Incentive Dynamic Engine (IDE). At least 50% of post-payout network revenue received in IO tokens will be permanently destroyed. Based on current earnings and its commercial pipeline, the company expects up to 12 million tokens to be burned during the first year.
Unlike projects that burn tokens based on transaction volume or fixed schedules, io.net ties the burn directly to on-chain revenue — the more the network earns, the more tokens get destroyed. Actual burn amounts may fall short if revenue disappoints.
Enterprise Deal and AI Inference Volumes Hit Records
io.net also disclosed its strongest commercial period to date. It signed an $8 million enterprise agreement, the largest contract so far, contributing roughly $650,000 in monthly on-chain network earnings. Additional enterprise deals are in advanced negotiations.
On the AI inference front, io.net has become the largest decentralized physical infrastructure network (DePIN) inference provider on OpenRouter, a platform for developers to access multiple AI models. The network now processes over 4 billion inference tokens daily, competing alongside centralized cloud providers.
These developments come as demand for AI computing resources keeps climbing. Citing industry spending trends, io.net noted that major tech companies have committed over $500 billion toward AI infrastructure across 2025 and 2026. The company argued that access to high-performance GPUs remains constrained by hyperscaler capacity limits and pricing, creating room for decentralized alternatives.
Stabilizing Supplier Earnings
Alongside the burn program, IDE addresses supplier retention challenges common in token-based networks. Supplier payouts are tied to a stable U.S. dollar value rather than fluctuating token prices. Reserve mechanisms absorb market volatility, allowing providers to maintain predictable earnings even during token price weakness, according to io.net.
Tokenomics research firm CryptoEcon Lab independently stress-tested the model. In simulations that included a 55% drop in demand and a 50% token price decline, supplier returns remained stable, per results cited by io.net.
“Most token economies in our space are still built around the hope that prices go up. Ours is built around the certainty that people are paying to use the network. That's a fundamentally different foundation,” said Gaurav Sharma, CEO of io.net.
Looking ahead, io.net said it is developing capabilities for AI agents to autonomously source and manage computing resources through its Agent Cloud platform. The company described this as part of building a self-sustaining on-chain compute economy supported by decentralized infrastructure providers worldwide.