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Multi-LLM Cost Optimizer is an AI LLM cost optimizer template that classifies each prompt by complexity and routes it to the cheapest model that can handle it, for developers who want to cut their AI API bills. Built on pydantic-ai and FastAPI, the template inspects an incoming prompt, scores its difficulty, and sends hard tasks to Claude while sending simple ones to a cheaper model such as Groq, with real-time cost tracking included. It works with Claude, GPT-4o, GPT-4o-mini, and Groq out of the box and is meant to drop into an existing project in under ten minutes. The package ships full source code, a test suite, and a setup walkthrough. It is one of about eleven pydantic-ai plus FastAPI templates published by the same author covering tasks like RAG APIs, document extraction, and support auto-responders, and templates or bundles are distributed through Gumroad. This is a developer code template rather than a hosted SaaS, so you self-host and supply your own model API keys. As an AI LLM cost-routing template, it suits engineering teams paying for multiple model providers who want per-request routing without writing the dispatcher themselves.

Developers use it to automatically route each prompt to the cheapest capable model and reduce multi-provider AI API costs.