Google Cloud API Gateway Ships Serverless Multi-Model Routing for Gemini and Claude
Google Cloud API Gateway now routes traffic across Gemini, Claude, and OSS models from a single OpenAI-compatible endpoint, no proxy servers required.
- Google Cloud API Gateway model routing is now in Public Preview, routing Gemini, Claude, and OpenAI OSS models from one endpoint.
- Routing logic lives in an OpenAPI 3.x spec using a new
x-google-api-managementextension block, no proxy server needed. - The gateway transcodes OpenAI-compatible payloads in-flight to each provider's native Vertex AI schema automatically.
- Key limits: same-host backends only, text modality only, no VPC Service Controls, no mixed routing configs in one spec.
- Pricing: first 2M gateway calls/month free, then $3.00/million; model inference billed separately through Vertex AI.
- Can be used standalone or chained with the Gemini Enterprise Agent Platform for full security governance.
Google Cloud API Gateway just shipped model routing in Public Preview. It targets one of the more tedious parts of building multi-model AI applications: managing a separate endpoint, SDK, and payload format for every model provider you want to use.
The proxy problem it replaces
The standard workaround today is running something like LiteLLM as a self-hosted sidecar. That gives you a proxy server to deploy, scale, monitor, and keep alive. API Gateway's model routing replaces that with a serverless ingress layer that accepts OpenAI-compatible requests and dynamically routes them to Gemini, Claude, or OpenAI-compatible models on Vertex AI. No proxy infrastructure to manage. The routing logic lives in your OpenAPI spec, and the gateway handles the rest at the network edge.
How routing actually works
When a request arrives, the gateway runs four steps in sequence:
- Intercepts the incoming
POST /chat/completionsrequest - Reads the
modelfield in the JSON payload (e.g.{"model": "claude-opus-4-7"}) - Matches that model name against routing rules defined in your OpenAPI 3.x spec, falling back to a default model if no rule matches
- Transcodes the OpenAI-compatible payload in-flight into the native Vertex AI schema, then dispatches it to the correct backend
That last step carries the real weight. Gemini, Claude, and OpenAI-compatible models each use different request and response schemas. The gateway translates between them transparently, so your client code stays the same regardless of which model is actually serving the request.