AI Cost Blog

Field-tested tactics to monitor, route, and shrink your AI API spend—without sacrificing output quality.

AI API Cost Monitoring: Track and Cut Spend

Set up AI API cost monitoring that catches token waste, retry spikes, and runaway agents before they hit your bill.

Batch API vs Real-Time: When Async Saves 50%

Batch APIs offer large discounts for asynchronous jobs. Learn when to route work to batch and when real-time is worth the premium.

Model Routing: When to Use Cheap vs Expensive Models

Model routing sends simple tasks to cheap models and reserves premium models for hard ones—often cutting cost without losing quality.

How to Estimate AI API Costs Before You Build

Estimate AI API cost from tokens and request volume before shipping, so you don't discover unusable unit economics after launch.

The Hidden Costs of AI Agents: Retries, Loops, and Tool Calls

Agents multiply cost through retries, tool chains, and non-converging loops. Learn to measure and cap the runaway parts.

Prompt Caching: How to Cut Repeat-Prompt Costs

Prompt caching can cut 50–90% of input token cost on repeated context. Learn how it works and when it pays off.