How Azure AI Gateway fits into Azure
Azure API Management can front AI backends and apply authentication, quotas, token controls, logging and other policies. Microsoft Foundry can integrate with that gateway layer so teams manage model access through Azure-native infrastructure.
This is different from a narrowly scoped LLM gateway whose only job is model-provider access. Azure's strength is integration with the rest of the Azure estate.
Azure AI Gateway cost drivers
Do not compare only the upstream model token price. The total architecture can include API Management capacity, networking, observability, security services, private connectivity and engineering operations in addition to model inference.
For an accurate comparison, price the exact Azure topology you would deploy and compare it against a managed or self-hosted LLM gateway serving the same workload.
When to choose Azure versus a dedicated LLM gateway
Azure is compelling when the organization already relies on Microsoft identity, networking, policy and monitoring and wants AI traffic governed in the same platform.
A dedicated LLM gateway may be easier when a small team primarily needs provider-direct BYOK, routing, fallback and spend visibility across several non-Azure model providers.