01
Confirm Preview fit
Use text-based OpenAI-compatible requests, model-tag routing, supported pre-deployed Vertex AI MaaS targets, and response SSE only.
Independent Preview planner · Source checked August 5, 2026
Plan one managed route from an OpenAI-style request to a Vertex AI model
API Gateway model routing can select configured Gemini, Claude, or OpenAI OSS-GPT targets from the request's model field. The Preview is a same-host, text-request routing layer—not a cross-provider proxy, policy engine, or proof that models behave interchangeably.
Five gates
A unified request shape does not make models interchangeable
02
Design one router
Map virtual model names to exact backend and target model values; keep every backend in that router on one Vertex AI hostname.
03
Deploy the config
Version the OpenAPI 3.x document, API config, gateway, project, location, credentials, and rollback artifact.
04
Apply controls
Set authentication, quotas or rate limits, token accounting, logs, budgets, data boundaries, and model-specific approval rules.
05
Test the contract
Verify default and explicit routes, payload transcoding, streaming, errors, missing models, unsupported protocols, and actual selected model.
Preview contract
request = text-based OpenAI-compatible JSON
selector = required model tag or name
targets = configured pre-deployed Vertex AI MaaS models
router_host = one global or one regional aiplatform hostname
streaming = server-sent response events only
unsupported = request streaming | gRPC | WebSockets | Gemini LiveContinue by deployment decision
Setup guide
Plan the Public Preview path from model inventory through deployment and rollback.
OpenAPI configuration
Define reusable backends, routers, route rules, and operation bindings.
Model targets
Map Gemini, Claude, and OpenAI OSS-GPT examples without implying cross-host routing.
Limits and troubleshooting
Diagnose one-host, model-field, modality, and streaming constraints.
Rate and token controls
Separate gateway limits, model quotas, token telemetry, budgets, and billing.
Agent Platform pairing
Combine Agent Gateway governance with API Gateway model routing without merging responsibilities.
API Gateway vs. Apigee
Choose lightweight Google-hosted model routing or a broader enterprise API program.
API Gateway model routing questions
It is a Public Preview managed routing layer that accepts text-based OpenAI-compatible prompt requests, uses the request model field to select a configured pre-deployed Vertex AI MaaS backend, and transcodes the request to the target schema.
Google's launch examples configure Gemini, Anthropic Claude, and OpenAI OSS-GPT models hosted through Vertex AI Model Garden. Exact model availability, region, quota, terms, and backend path must be verified when deploying.
No. Google documents that all backends referenced by one router must share one hostname, such as the global aiplatform.googleapis.com host or one regional Vertex AI hostname.
No. It is an independent implementation planner. It does not access a Google Cloud project, create credentials, deploy an API config, route requests, or establish a Flowith integration.
Official references: Google Developers Blog launch, model routing overview, and OpenAPI 3.x extensions.