AWS shows how to evaluate model routing for coding agents

AWS has published a November 13 walkthrough for routing coding-agent requests across models on Amazon Bedrock. The example combines the open-source NVIDIA NeMo Switchyard router with LiteLLM, then compares routed runs against single-model baselines.

The useful question is not simply which model has the lowest token price. An agent may need extra turns or retries to finish a task. AWS suggests comparing cost per solved task and the number of tasks solved, while examining hard tasks separately. Its small sample is intended to demonstrate the workflow, not establish a general cost or quality advantage.

Experimental sample, real costs

In the described setup, stage routing selects between two candidates using recent tool activity and results; a separate random strategy enables weighted traffic splits. AWS calls this particular LiteLLM integration experimental and says the example is for non-production use. Cloud infrastructure and model calls incur costs.

The benchmark runners execute generated Python, and AWS warns that their subprocess is not an operating-system sandbox. It recommends an isolated environment without long-lived credentials. That matters even when an example removes credentials from the subprocess environment: generated code may still access files or the network.

Switchyard's source is available through our repository profile. We have not deployed the sample, run its benchmarks or independently measured any savings.