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On June 11, 2023, io.net launched with a straightforward idea. AI workloads need more compute than centralized hyperscalers can ever deliver, and the solution would be a decentralized network of GPUs, not another mega data center, that turns underutilized capacity into on-demand infrastructure. Three years later, we’ve fundamentally changed the AI compute market. io.net is now the largest decentralized GPU network in the world. Thousands of GPUs distributed globally, with $8 million in enterpri
Three years ago, we started io.net with a simple, powerful belief that the infrastructure behind AI shouldn't be in the hands of a few giant corporations. Today, we're taking a huge step toward making that vision a reality. As we celebrate our third anniversary, we're excited to announce the official launch of the Incentive Dynamic Engine (IDE). It's a new way of thinking about our tokenomics that ties the supply of $IO directly to how much people are actually using the network. We'll be perman
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RunPod has a reputation for being the GPU solution for the "instant-deploy" developer. Its intuitive "Pods" and robust serverless GPU offerings make it a good fit for startups and hobbyists who frequently prototype. Whereas legacy providers focus on enterprise contracts and academic researchers stick to boutique clouds, RunPod captured the mid-market by mastering serverless GPU compute and container-based flexibility. Its reputation is built on "FlashBoot" technology (sub-200ms cold starts) and
GPU cloud costs have climbed steadily since 2022, and most developers don't really understand why. An NVIDIA H100 SXM on AWS (p4d.24xlarge equivalent) runs roughly $32–$36/hr on-demand. The same GPU on io.net costs $2.99/hr. That amounts to a 10x gap.
On June 11th, io.net's third anniversary, we launched the Incentive Dynamic Engine (IDE). Not a roadmap, not a litepaper. Live, on-chain, utility driven, and fully transparent. A month in, here's another look at what the IDE is, why it matters, and what's happened since. What the IDE does Most token networks grow the same way. They pay suppliers with emissions, and hope demand eventually catches up to justify the supply. It works until it doesn't. When the token price drops, suppliers leave
For infrastructure decision-makers at both startups and growing companies, the GPU landscape of 2026 looks nothing like it did even last year. The mad dash for GPU capacity has now matured into a $140B+ global market defined by architectural diversity, pricing pressure, and a fundamental reevaluation of how compute should be provisioned. As these three forces converge, we are seeing GPU supply expand. While hyperscaler buildouts capture a lot of attention, there has also been a rise in decentr
The AI landscape of 2026 is now more of a battle of over infrastructure instead of a clash of models. For many AI/ML developers, CoreWeave has been the reliable "specialized" choice for NVIDIA hardware. However, as the "Power Wall" of 2026 makes electricity and high-density data center space more precious than the chips themselves, many startup and enterprise teams are searching for alternatives that offer both better availability and more affordable pricing. So, if you’ve been priced out by Co
Frontier AI training, or models with 70B+ parameters, multimodal architectures, MoE variants, requires GPU clusters operating at a scale most teams just can’t self-host. On io.net, AI teams don’t even have to think about self-hosting your compute, or paying hyperscaler prices. You can effortlessly spin up a distributed cluster of H100s or A100s in minutes, paying $1.49–$2.29/hr per GPU with no reserved-capacity commitment. Instead of all of the overhead costs that come with self-hosting, you c
Your 2026 guide to building a purpose-built GPU cluster for AI. Includes TCO, vendor-agnostic benchmarks, hardware selection (H100/MI300X), and rollout plan.
Z.ai's GLM-4.7-Flash (30B MoE) is live on io.intelligence. Get the strongest 30B model for coding & reasoning with best-in-class performance-per-dollar.
Complete technical guide to decentralized compute: benchmarks, cost calculator, compliance checklist, and step-by-step migration from AWS/GCP.
Learn what a GPU cluster is, how it differs from multi-GPU servers, and use our cost calculator to decide if you should build or rent one.
Your 2026 guide to building a purpose-built GPU cluster for AI. Includes TCO, vendor-agnostic benchmarks, hardware selection (H100/MI300X), and rollout plan.
Complete technical guide to decentralized compute: benchmarks, cost calculator, compliance checklist, and step-by-step migration from AWS/GCP.
Discover io.net's Incentive Dynamic Engine (IDE): an adaptive tokenomics model bringing sustainable economics and predictable stability to decentralized GPU compute.
New io.net study shows consumer GPUs (RTX 4090) can cut AI inference costs by up to 75% for LLMs, enabling a sustainable, heterogeneous compute infrastructure.
Blockchain promised to solve centralization, but focused on wrong problems. DePIN networks like io.net finally deliver real value through affordable GPU access.
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Tired of 25-call limits killing your AI coding flow? Learn how io.net and Void Editor unlock truly autonomous development without artificial constraints.
io.net launches Total Network Earnings (TNE) for complete transparency in AI infrastructure costs with real-time tracking, automated payments, and verifiable metrics.
io.net celebrates its first anniversary, showcasing growth to 10,000+ GPUs across 138 regions and $13M revenue while democratizing AI infrastructure access.
io.net enables privacy-first AI training through Flashback Labs' Stargazer model, using federated learning and TEEs to protect personal data during training.
Launch I/O is a 35-day hackathon where developers build autonomous AI agents using io.intelligence's unified toolkit, with $6,500 in prizes and ecosystem access.
Injective partners with io.net to revolutionize DeFAI development by combining AI-driven blockchain tools with decentralized GPU computing infrastructure.
Theoriq partners with io.net to power decentralized AI agent swarms on blockchain, reducing compute costs by 90% while scaling modular AI ecosystems.
io.net's developer tools provide simplified API integration and decentralized GPU access, reducing AI deployment costs by up to 90% compared to centralized providers.
Explore how decentralized computing networks are revolutionizing AI development by providing cheaper, faster, and more scalable alternatives to traditional cloud services.
A comprehensive guide to launching and managing virtual machines and containers on IO.net's decentralized GPU cloud platform for cost-effective computing.
A comprehensive guide to launching and managing virtual machines and containers on io.net's decentralized GPU cloud platform for cost-effective computing.
IO Intelligence is an AI-powered analytics system that optimizes decentralized computing with real-time monitoring, cost reduction, and LLM performance tracking.