LLM Model Routing: Cut AI API Costs by 80 Percent

LLM model routing cost optimization: stop paying frontier prices for every request and cut your AI API bill by 40 to 80 percent without capping access or slowing your team down. In June 2026, Coinbase CEO Brian Armstrong revealed that his company cut its internal AI spend nearly in half while token usage kept growing, by deploying an LLM gateway that routes each request to the cheapest capable model and pushed its cache hit rate from 5 percent to 60 percent. That real-world result lines up with peer-reviewed research: the RouteLLM paper, published at ICLR 2025 by LMSYS, demonstrated 85 percent cost savings while retaining 95 percent of frontier-model quality. This video breaks down exactly how LLM routing works, the three routing strategies every team should know, and which tools to use to build it yourself today. In this video: - What an LLM router (AI gateway) is and how it intercepts and routes every model request - The Coinbase LLM gateway playbook: smarter defaults, task-based routing, and aggressive caching - Three routing strategies compared: rule-based routing, complexity classifier, and cascade routing - LiteLLM vs Portkey vs OpenRouter: which LLM gateway tool fits your stack in 2026 - A practical five-step checklist to implement LLM cost optimization in your own application Subscribe to Webronaq for clear, practical lessons on computer science, AI, and software engineering: https://www.youtube.com/@Webronaq #LLMmodelrouting #AIcostoptimization #LLMgateway #AIProgramming #Webronaq