[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"glossary-model-router::en":3,"gloss-cluster-model-router::en":26,"gloss-next-model-router::en":9},{"slug":4,"category":5,"name":6,"definition":7,"meta_desc":8,"faq":9,"schema_markup":9,"related":10},"model-router","core-ai","Model Router","A model router is a layer that decides which model should handle each request, instead of sending everything to one model. Routing can be rule-based (short classification goes to a cheap model; a long code task goes to a reasoning model), driven by a small classifier that predicts difficulty, or steered by the prompt itself. The goal is to hit a target quality at the lowest cost and latency: most requests are easy and go to a fast, cheap model, while the hard minority get escalated to a powerful, expensive one. For SaaS builders, a router is one of the highest-leverage cost optimizations available — teams routinely cut LLM spend by half or more without users noticing, because they stop paying frontier-model prices for trivial calls. Practical concerns: you need evals proving the cheap model is actually good enough on the routed traffic, a fallback path when it fails, and monitoring so drift in your traffic mix doesn't quietly degrade quality. Several managed routing services and open-source libraries now do this for you.","A model router decides which model handles each request — cheap models for easy work, frontier models for hard reasoning — cutting cost without losing quality.",null,[11,14,17,20,23],{"slug":12,"name":13},"latency","Latency",{"slug":15,"name":16},"llm","Large Language Model (LLM)",{"slug":18,"name":19},"reasoning-model","Reasoning Model",{"slug":21,"name":22},"small-language-model","Small Language Model (SLM)",{"slug":24,"name":25},"test-time-compute","Test-Time Compute",[27,31,35,39,42,45,48,51,54,57,60,63],{"slug":28,"category":5,"name":29,"updated_at":30},"agentic","Agentic AI","2026-08-24T02:46:36+00:00",{"slug":32,"category":5,"name":33,"updated_at":34},"alignment-tax","Alignment Tax","2026-08-24T02:46:37+00:00",{"slug":36,"category":5,"name":37,"updated_at":38},"artificial-intelligence","Artificial Intelligence (AI)","2026-08-24T02:46:38+00:00",{"slug":40,"category":5,"name":41,"updated_at":30},"attention","Attention",{"slug":43,"category":5,"name":44,"updated_at":38},"beam-search","Beam Search",{"slug":46,"category":5,"name":47,"updated_at":34},"benchmark-contamination","Benchmark Contamination",{"slug":49,"category":5,"name":50,"updated_at":34},"catastrophic-forgetting","Catastrophic Forgetting",{"slug":52,"category":5,"name":53,"updated_at":38},"computer-vision","Computer Vision",{"slug":55,"category":5,"name":56,"updated_at":34},"constitutional-ai","Constitutional AI",{"slug":58,"category":5,"name":59,"updated_at":30},"context-window","Context Window",{"slug":61,"category":5,"name":62,"updated_at":38},"deep-learning","Deep Learning",{"slug":64,"category":5,"name":65,"updated_at":30},"diffusion-model","Diffusion Model"]