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.
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.
KayOS, an AI startup, achieved 5x developer power with io.net. Learn how their 2-person team cut compute costs by 60% ($2.5k to $1k/month) using io.intelligence.
![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.
KayOS, an AI startup, achieved 5x developer power with io.net. Learn how their 2-person team cut compute costs by 60% ($2.5k to $1k/month) using io.intelligence.
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.
Unified Chat is the single, intelligent AI workspace that unifies every model and tool. Auto-routes for optimal quality and cost. End fragmentation.
Complete financial framework for GPU infrastructure decisions. Cost modeling, ROI analysis & budget optimization for AI companies.
Model deployment connects trained ML models to users, yet most stall due to cloud costs and vendor lock-ins. Decentralized platforms cut costs 90%.
io.net is leveraging smart contracts on the Solana blockchain to automate GPU rentals, payments, and resource allocation for transparent decentralized computing.
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.
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.
io.Intelligence delivers real-time monitoring for AI workloads, helping optimize performance, cut costs, and ensure reliable system stability.
"IO.net offers a decentralized GPU cloud, enabling scalable, cost-effective AI training, rendering, and simulations with global resources."
