How to Build an LLM Router That Routes by Complexity

An LLM router sits between your application and model providers, evaluating incoming requests dynamically to select the most appropriate model. Instead of binding every call to a single frontier model, a complexity-based router sends routine extraction or short factual tasks to cost-effective models while reserving high-end reasoning systems for complex tasks. This tutorial demonstrates how to configure and deploy a complexity router using Bifrost, an open-source LLM gateway built in Go, ensuring seamless integration without modifying your core application code.

Understanding LLM Routing Strategies

Most engineering teams start by hardcoding a single model per call site. While simple, this approach fails when a single endpoint—such as a developer chat assistant—receives both trivial greeting messages and highly intricate debugging requests. Over-provisioning leads to inflated API bills, while under-provisioning degrades response quality.

Modern API gateways solve this dilemma through dynamic routing. The table below compares common routing paradigms:

Approach	How the Model is Chosen	Best Suited For	Key Limitation
Hardcoded	Developer selects one model in code	Uniform endpoints	Overpays for easy requests, underserves hard ones
Header/Metadata	CEL rule on headers, team, or request type	Routing by tenant, region, or environment	Blind to actual task difficulty
Complexity Router	Classifier assigns a tier; CEL rules map tiers to models	Chat, assistants, and agents with mixed difficulty	Adds one classification call per routed request

Configuring the Decision Model Classifier

Bifrost v2.3.0 introduces native complexity routing, supporting two primary classifiers: a decision model and a semantic classifier. The decision model uses a dedicated lightweight LLM (such as Typesafe Jev by default) to evaluate the request against specific tier definitions.

To configure the decision model, update your gateway configuration file:

\{
  "governance": \{
    "complexity_analyzer_config": \{
      "classifier": "decision

Source: https://dev.to/kuldeep_paul/how-to-build-an-llm-router-that-routes-by-complexity-3p5c