Learn how to build a Multi-Model LLM Routing System that reduces AI infrastructure costs while improving performance and scalability in 2026. This guide explores intelligent model routing, dynamic AI model selection, request orchestration, and cost optimization strategies for enterprise AI applications. Discover how to route tasks to the most suitable language models based on complexity, latency, and pricing to maximize efficiency. Whether you're developing AI agents, chatbots, or enterprise automation solutions, implementing a multi-model architecture helps reduce token usage, optimize inference costs, improve reliability, and deliver faster, more accurate AI-powered experiences at scale.