Multi-Model Routing Workflow

Objective

Automatically send each request to the cheapest model capable of handling it, instead of routing every query — simple or complex — to your most expensive flagship model. This workflow outlines how to set up routing logic that cuts blended costs without a noticeable quality drop on easy tasks.

Prerequisites

• API access to at least two models of different price/capability tiers (e.g. a budget and a flagship model from the same or different providers).
• A way to classify incoming requests by complexity — this can be as simple as prompt length and keyword rules, or a lightweight classifier model.
• Basic scripting or a workflow/automation tool (n8n, Zapier, or custom code) to implement the routing logic.

Tools

Any two models with an API (mixing providers is fine), plus your existing application code or an automation platform to sit in front of the model calls.

Workflow steps

1. Classify the request. Use simple heuristics first: short, single-step requests (classification, extraction, short replies) route to the budget model. Long-context, multi-step, or reasoning-heavy requests route to the flagship model.
2. Route the call. Send the request to whichever model tier the classification step selected.
3. Set a fallback. If the budget model’s response looks low-confidence or fails a basic quality check, automatically retry with the flagship model rather than returning a weak answer.
4. Log the routing decision. Track which tier handled each request and its outcome, so you can refine the classification rules over time.
5. Review and tune monthly. Adjust your routing thresholds based on where the fallback rate is highest — that’s usually a sign the budget model is being asked to handle tasks it shouldn’t.

Inputs and outputs

Input: incoming user or system request. Output: a model response plus a routing log entry (which model handled it, and whether a fallback was triggered).

Automation options

Simple keyword/length-based routing can be implemented in a few lines of code in front of your existing API calls. More sophisticated setups use a small, fast classifier model to score request complexity before routing — this adds a small latency and cost overhead but improves routing accuracy for less obviously simple/complex requests.

Optimization tips

• Start conservative — route only the most obviously simple requests to the budget model, then expand as you build confidence in the quality gap (or lack of one) for your specific use case.
• Combine with prompt caching on the flagship model for further savings on the requests that do need it.
• Track cost-per-resolved-request, not just cost-per-call, since fallback retries add cost that raw call-volume savings can hide.

Related resources

See the Cost-to-Performance Ratio Analysis for data on where budget models hold up, and the API vs Subscription Cost Calculator to estimate savings.