IO.NET (IO)

♟️ IONET unveiled a new tokenomics model $IO announced a new economic model based on an Incentive Dynamic Engine (IDE). How it works: 👉 the token supply adjusts according to the network’s actual activity 👉 if revenue exceeds payments, tokens are burned 👉 if revenue is insufficient, the supply can increase temporarily Other key points: • at least 50% of net revenue is burned • payments to suppliers are denominated in USD • goal: align revenue, usage, and token issuance

Today we’re turning a page in @ionet’s story. We’re moving from tokenomics that helped us bootstrap to a demand-driven, self-regulating economy we call the Incentive Dynamic Engine (IDE). This shift is about building a network that can last decades, not just quarters. - What We Had to Outgrow - Our first token model did its job: it helped us bootstrap supply. But it also carried the classic tradeoff - fixed emissions mean persistent inflation and weak coupling to real usage. When incentives are too detached from demand, you get fragility. Most importantly, supplier income was exposed to token volatility. In a downturn, this could trigger a negative feedback loop: Price falls → supplier ROI falls → suppliers leave → network utility weakens. We cannot have a compute network that’s only healthy when markets are euphoric. So we rebuilt the incentive layer from the ground up. - What's the IDE? - Think of the IDE as a real-time economic controller for decentralized compute. Instead of “emit tokens and hope demand catches up,” the IDE uses actual GPU utilization and real revenue to shape rewards, supply dynamics, and long-term token supply. We’re shifting from an inflationary, supply-driven model to a demand-driven system that stabilizes supplier payouts and ties $IO value to real network activity. - Under the Hood: IDE Fundamentals - - Two Vaults - We introduced two new "buffers" between fluctuating demand/revenue and stable supplier payouts: ◼ Reward Vault — holds $IO emissions. ◼ Fee Vault — holds fees from real users who consume compute. When paying suppliers, the system draws from these vaults in this order: ◼ Reward Vault – first, payouts are funded with $IO emissions. ◼ Fee Vault – next, the system uses fees collected from compute users. ◼ If the combined flow can’t sustainably support target payouts, the IDE adjusts parameters (like hardware pricing or target ROI) to protect the long-term health of the network. These vaults act as shock absorbers: they smooth out fluctuations in token price, demand, and payment cycles so suppliers can rely on stable, USD-denominated earnings even when conditions are unpredictable. - Why Supplier Earnings Are Now Predictable - Suppliers will earn in stable USD terms, but receive those payout amounts denominated in $IO tokens. This protects the people providing real infrastructure from short-term swings, which is critical if you want professional-grade, long-term compute supply. - The Health Metric to Watch - We’re introducing a simple transparency anchor: ψ = Revenue (R) / Payout obligations (H) ψ > 1 → surplus → burns/deflation ψ = 1 → stable equilibrium ψ < 1 → temporary expansion/buffering to protect suppliers This is the clearest mathematical signal that @ionet’s economy is now being driven by actual utility. - What This Upgrade Enables for Everyone - ◼ For Suppliers You get predictable earnings tied to real economic activity, not pure token volatility. We believe this attracts long-term, professional infrastructure partners - not short-term opportunists. ◼ For Users You get a network that stays online across market cycles - a key requirement for startups, scale-ups, and enterprises who need stability. ◼ For Token Holders The IDE introduces a deflationary orientation: part of net revenue is designed to be burned, enabling a meaningful long-term supply reduction. - What This Means for the Entire Sector - DePIN needs higher standards to move from infancy to maturation. Most networks in this space still rely on the same early-stage logic: heavy emissions and light demand coupling. The IDE is our attempt to prove that decentralized networks can be stable, resilient, and utility-first - not just exciting during bull markets. - Governance, Reality, and Risk - This is not designed as a "set-and-forget" system. Governance will monitor: > the sustainability ratio > reserve runway > vault balances > and total burns Risks include moral hazard, reserve drift, and reflexive dynamics - but these are mitigated through: > circuit breakers > diversified reserves > dynamic parameter adjustment We used emissions to bootstrap the network. Now we’re building an economy that self-regulates around real usage, protects suppliers, and offers predictability for users, developers, and enterprises. If decentralized compute is going to be a real backbone for AI, it can’t be powered by market sentiment and hope. It has to be powered by usage, resilience, and a model that works in every market environment. That’s what the IDE is for.

Most Depin projects fall apart once their token price goes down @ionet fixed a big problem in crypto When customers pay for GPU → $IO tokens get destroyed (less supply = better for holders) GPU owners get paid in stable dollars (no worrying about token prices jumping around) Half of all profits go to burning tokens (permanently removing them) Only creates new tokens when absolutely needed (no endless printing) Why this matters: Most crypto projects print tokens non‑stop until they collapse. ionet built theirs to survive, even in crashes. The proof: $21.3M+ earned (you can check it on-chain) 3,000+ GPUs ready to work across 130+ countries Real partners: Walrus, Nillion, Injective

It's no argument that DePIN is positioned at the 1st place by reward-optimized route to users. However, regular tokenomics models are still not able to handle this. @ionet fixes this with Incentive Dynamic Engine (IDE). tl;dr: + IDE splits up the vault into 2 pieces: reward and fee + a ratio mechanism of burn and store is used to keep these vaults balanced ➜ The result lies in how $IO supply is optimized and ties IO token value directly to real usage. For instance, IDE helps route the computing cost directly to the hardware providers. IDE suits not only IOnet; it's built for sustainable DePIN models.

#Roadmap 🇬🇧 #ioNet ( $IO ) — Complete Roadmap 🧵 From tackling AI infrastructure bottlenecks to building the world’s largest decentralized GPU network, #ioNet has evolved remarkably fast. Here’s the complete journey: Past → Present → Future #CryptoRoadmap 📜 Past: Development & Launch https://t.co/ONQB5nrMFI, originally known as ANTBIT, was established in 2022 by a team of seasoned professionals with expertise in cryptocurrency exchanges and quantitative finance, addressing high-cost cloud computing and real-time market data challenges. Key Milestones: 🔹 Early Development Phase Founding team integrates open-source distributed computing libraries inspired by large-scale AI training to accelerate infrastructure for low-latency operations across CPUs and GPUs. 🔹 Shift to Decentralized GPU Network Project pivots to a DePIN model, aggregating idle GPU resources globally to support AI tasks like model serving and hyperparameter tuning. 🔹 Core Verification Mechanisms Introduction of Proof-of-Work (PoW) and Proof-of-Time-Lock (PoTL) protocols to ensure node reliability and honest participation. 🔹 V1.0 Full Release Platform achieves its first major release, transitioning to a community-influenced development cycle with feedback-driven updates. 🔹 Staking & Incentive Protocols Launch of staking systems to reward contributors and solidify https://t.co/ONQB5nrMFI as a foundational layer for accessible AI compute. Impact: From a centralized AI infrastructure initiative to a decentralized GPU network, https://t.co/ONQB5nrMFI set the stage for scalable, community-driven AI computing. #ioNetHistory ⚡ Present: Current Status & Developments https://t.co/ONQB5nrMFI today operates as a mature decentralized GPU marketplace, orchestrating workloads globally via IO Cloud, IO Intelligence, and IO Worker. Ecosystem Expansion: Partnerships with Allora Network, GAIB, Oortech, FrodoBots, ChainGPT, and Phala Network expand use cases into AI, DeFi, and zero-knowledge infrastructure. Technical Progress: Enhanced interoperability via standardized container templates and optimized APIs enables seamless inference and fine-tuning across distributed clusters. Governance & Incentives: Progressive decentralization introduces community-led DAOs and token-based voting, while IO Staking and IO ID simplify participation and earnings management. Ecosystem Challenges: Managing global hardware resources, coordinating distributed AI workloads, and ensuring secure network governance remain ongoing priorities. #ioNetNow #DePINGrowth 🚀 Future: Planned Roadmap (2025–2030+) https://t.co/ONQB5nrMFI’s future focuses on infrastructure scaling, ecosystem growth, and fully decentralized governance. Key Roadmap Directions: 🔹 HyperGPU Clusters Advanced distributed computing clusters to handle large-scale AI workloads efficiently. 🔹 AI Marketplace Expansion Connecting developers with specialized tools, pre-trained models, and autonomous agents for broader adoption. 🔹 Software Frameworks & Education Standardizing distributed AI applications through new frameworks and educational resources. 🔹 Enhanced DAO Integrations Community-driven feature voting, staking multipliers for diverse hardware, and global developer community initiatives. 🔹 Proof-of-Inference & Self-Sustaining Governance Verifiable AI outputs and fully autonomous governance for a robust decentralized ecosystem. Impact: Faster deployment of AI workloads, broader developer adoption, decentralized governance, and global-scale scalability across distributed systems. Risks & Opportunities: While decentralized infrastructure and emerging compute paradigms pose operational challenges, https://t.co/ONQB5nrMFI’s technical maturity and community focus provide strong long-term potential. #ioNetFuture #AICompute ✅ Conclusion https://t.co/ONQB5nrMFI has transformed from a centralized quantitative computing initiative into a fully decentralized GPU network enabling autonomous AI development and Web3 experimentation. With innovations like HyperGPU clusters, IO Cloud, DAO governance, and ecosystem partnerships, $IO lays the foundation for scalable, cost-efficient, and democratized AI infrastructure. #RoadmapConclusion 🛒 Want to trade $IO on #WEEX? 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#IO The descending wedge continues . . I will keep monitoring for a while longer and will provide detailed buying information later. https://t.co/YNKSXeRomL