AI Model Routers

AI model routers choose where an inference request is sent. Selection may be fixed by developer rules or automated according to task, quality, price, latency, capacity or availability. This tag requires routing between meaningful model or provider options, not a simple API proxy.

Test routing behavior

Check whether you can pin models and providers, set priorities, exclude regions, limit spend and control fallbacks. Evaluate retries, load balancing, health signals and how model identity appears in logs. Automatic selection should be measured with your own prompts because cheaper or faster is not always accurate enough.

Data and operational risk

A routed request may pass through more than one organization. Review each party’s retention and training policies, key management and regional controls. Compare routing fees and confirm how outages, model changes and deprecated routes are communicated.

Common question

Is routing the same as using many models?

No. Multi-model access offers a catalog; routing adds logic that selects or switches the execution path.