Model Routing
Sending each request to the cheapest model that can handle it.
/ quick answer
A router classifies the task (simple/hard, short/long, code/prose) and dispatches to a small model (Haiku, GPT-4o mini) or a large one (Sonnet, GPT-4o). Cuts cost 5-10x with no visible quality loss. Sending each request to the cheapest model that can handle it.
/ frequently asked
What is Model Routing?
A router classifies the task (simple/hard, short/long, code/prose) and dispatches to a small model (Haiku, GPT-4o mini) or a large one (Sonnet, GPT-4o). Cuts cost 5-10x with no visible quality loss.
What is an example of Model Routing?
A support bot routes FAQ matches to a small model and only escalates ambiguous queries to Sonnet.
Why does Model Routing matter?
Sending each request to the cheapest model that can handle it.
What should I learn after Model Routing?
Open the related workflows and prompts further down this page: they show how this idea is applied in a real task, step by step.
/ continue exploring
Related concepts
The vocabulary this page depends on.
- →AI Router
A layer that picks the cheapest capable model for each request, saving cost and latency.
- →Quantization
Shrinking a model by lowering weight precision.
- →Inference
Running a trained model to produce outputs.
- →MCP (Model Context Protocol)
Open protocol that lets LLMs connect to tools, data sources and apps through a standard interface.
Related workflows
Turn this into a repeatable process.
- →How to Create a Website with AI
Go from idea to a live, custom-domain website in one afternoon using AI builders.
- →How to Build an AI Content System
A repeatable pipeline that turns one input into publish-ready content across every channel.
- →How to Start a Niche Website with AI
Pick a niche, validate demand, build the site, and publish ranking content using AI end-to-end.
- →Personal Research Assistant Workflow
A repeatable system to research any topic deeply in under 30 minutes.
Related tool stacks
The tools that run it in production.
- →AI Cost Optimization Stack
This stack provides tools and services for monitoring, analyzing, and controlling the operational costs associated with AI agent deployment and LLM usage.
- →AI Research & Knowledge Stack
Default toolset for analysts, founders and creators doing deep research with AI.
Related prompts
Reusable prompts for this job.
- →Model Routing Classifier Prompt
A cheap-model prompt that labels request difficulty so it can be routed to the right model.
Comparisons & alternatives
Pick between the options.
- →Groq vs Together AI
Fast open-model inference: throughput vs breadth.
- →Chroma vs Qdrant vs Pinecone
Open-source local vs managed cloud vector databases.
- →ChatGPT vs Claude
Two leading conversational AI assistants compared across reasoning, writing, coding, and pricing.
- →Lovable vs Bolt
Two AI app builders compared on speed, backend, deployment, and production readiness.