AI Infrastructure & Compute
Technical reference for GPU rental markets, data center capacity economics, decentralized compute networks, and AI infrastructure financing structures.
Revenue Models & Economics
Pricing structures, utilization optimization, and market dynamics for GPU compute and data center capacity.
GPU Rental Economics
Spot, reserved, and dedicated pricing models for GPU compute—utilization optimization, provider margins, and market segmentation.
Compute Token Mechanics
Token-based payment systems, staking mechanisms, and rewards structures in decentralized GPU networks like Render and io.net.
Data Center Capacity Markets
Wholesale versus retail colocation pricing, power constraints, and geographic capacity allocation for AI deployments.
AI Inference vs Training Economics
Cost structures and margin profiles for model training versus inference serving—capital intensity and operational differences.
Infrastructure Structures & Agreements
Financing mechanisms, hosting agreements, and facility leasing structures for AI infrastructure deployment.
GPU Collateralization
Asset-based lending using GPUs as collateral—advance rates, CoreWeave's $7.5B facility, and liquidation mechanics.
Decentralized Compute Networks
Architecture and economics of distributed GPU marketplaces—Render, io.net, Akash coordination mechanisms and node incentives.
AI Model Hosting Agreements
Revenue sharing structures, SLA requirements, and liability allocation in model deployment contracts.
Hyperscale Data Center Leasing
Triple-net lease structures, power purchase agreements, and economics of 20MW-200MW facilities for AI infrastructure.
Risk Analysis & Market Dynamics
Hardware depreciation patterns, demand volatility, and capacity planning challenges in AI infrastructure markets.