See how Leonardo.Ai scaled from 14K to 19M users and cut GPU costs by over 50% using io.net's high-performance, affordable compute solution for generative AI.
Complete comparison of GPU vs CPU for AI: deep learning performance, hardware cost, TCO, and ideal use cases. Choose the right processor for your training and inference workloads.
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.
18 production-ready AI agents for NLP, market data, & automation on io.intelligence. Consolidate your AI stack with one API.
Complete technical guide to decentralized compute: benchmarks, cost calculator, compliance checklist, and step-by-step migration from AWS/GCP.
Your GPU data center investment framework. Compare TCO for cloud, colo, & workstation, including power, cooling, ROI, and hidden costs.
GLM-4.7 is now live on io.intelligence. Z.ai's open-source coding model scores 84.9% on LiveCodeBench vs Claude's 64%. Access it via a single API endpoint.
io.net's 2025: $4M+ saved across 5 case studies, 320K GPUs in 138 countries, 21 partnerships, and a tokenomics redesign. What happens when infrastructure stops being the constraint.
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.
GLM-4.7 is now live on io.intelligence. Z.ai's open-source coding model scores 84.9% on LiveCodeBench vs Claude's 64%. Access it via a single API endpoint.
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.
Discover io.net's Incentive Dynamic Engine (IDE): an adaptive tokenomics model bringing sustainable economics and predictable stability to decentralized GPU compute.
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.
![AI Training vs Inference: Key Differences, Costs & Use Cases [2025]](/_next/image?url=https%3A%2F%2Fio-net.ghost.io%2Fcontent%2Fimages%2F2025%2F11%2Fio-Blog-AI-Inference-vs-Training.png&w=640&q=75)
AI training teaches models to recognize patterns. AI inference applies those models to make predictions. Learn the differences, costs, and optimization strategies in io.net’s complete guide.
Complete comparison of GPU vs CPU for AI: deep learning performance, hardware cost, TCO, and ideal use cases. Choose the right processor for your training and inference workloads.
Wondera cut AI training costs 75% and scaled to 200,000 users in 4 months using io.net's decentralized GPU infrastructure, launching 3 months ahead of schedule.
Blockchain promised to solve centralization, but focused on wrong problems. DePIN networks like io.net finally deliver real value through affordable GPU access.
Unified Chat is the single, intelligent AI workspace that unifies every model and tool. Auto-routes for optimal quality and cost. End fragmentation.
Vistara Labs used io.net to scale its Zaara AI platform, building 5,600 apps in two months while cutting compute costs by 3x and achieving zero infrastructure failures.
Complete financial framework for GPU infrastructure decisions. Cost modeling, ROI analysis & budget optimization for AI companies.
io.net surpasses $20M in verifiable on-chain revenue, proving decentralized GPU infrastructure can compete with AWS and GCP on cost, performance, and real-world adoption.
Model deployment connects trained ML models to users, yet most stall due to cloud costs and vendor lock-ins. Decentralized platforms cut costs 90%.
Discover how AI data centers optimize workloads, boost efficiency, and power the future of artificial intelligence with advanced infrastructure.
Forget AWS's $37/hour GPU costs. Decentralized networks deliver the same power for 50-70% less, turning idle gaming rigs into AI supercomputers.
Learn how io.net evolved from trading infrastructure to decentralized GPU cloud computing, using distributed resources and blockchain for scalable AI.
