AI Gateway vs API Gateway vs Gateway API: what's the difference
AI Gateway, API Gateway, and Gateway API are three terms that sound alike but serve distinct purposes. An API Gateway sits between a client and backend services, handling common tasks like , rate limiting, and logging in one place. An AI Gateway builds on that concept with features specific to : it lets you connect to multiple AI providers (such as OpenAI, Anthropic, or Gemini) through a single interface, and adds token usage tracking, cost management, , and (automatically switching to a backup model if the primary one fails).
Gateway API, by contrast, is a Kubernetes networking standard unrelated to AI. For anyone running AI agents or LLM-powered services, an AI Gateway offers a practical way to manage multiple models, control spending, and improve reliability from one central layer.
Key points
- An AI Gateway unifies multiple AI providers behind one interface, making it easy to switch models
- Token usage and costs can be tracked and controlled centrally
- reuses previous results to avoid redundant API calls and reduce costs
- automatically switches to a backup AI model if the primary one is unavailable
- Gateway API is a Kubernetes networking spec — unrelated to AI gateways despite the similar name