Google Cloud API Gateway now offers a model routing feature in Public Preview, allowing developers to dynamically route traffic to models like Gemini, Claude, or OpenAI OSS-GPT without hardcoding endpoints or managing open-source proxies. Developers can easily configure these routing rules directly within their OpenAPI 3.x specifications by mapping virtual model names to specific backend targets on a shared host. Once deployed, the Gateway acts as a serverless ingress layer that accepts standard OpenAI-compatible requests, automatically transcodes the payload to the native schema of the target model, and routes the traffic on the fly.
Overview of model routing | API Gateway | Google Cloud Documentation
Model routing for API Gateway is a managed traffic management layer that accepts OpenAI-compatible prompt requests, transcodes them in-flight, and routes them to specific Gemini Enterprise Agent Platform models. Model routing acts as a managed alternative to client-side proxies such as LiteLLM, providing centralized infrastructure to manage the lifecycle of AI agents.
OpenAPI 3.x Extensions in API Gateway | Google Cloud Documentation
API Gateway accepts a set of Google-specific extensions to the OpenAPI specification that configure the behaviors of the gateway. These extensions allow you to specify API management settings, authentication methods, quota limits, and backend integrations directly within your OpenAPI document. Understanding these extensions helps you tailor your service behavior and integrate with API Gateway features.
AI gateway capabilities | Apigee | Google Cloud Documentation
Learn how to use Apigee AI gateway features to govern, optimize, and scale AI traffic.
Ambassador: Building a Control Plane for an Envoy-Powered API Gateway on Kubernetes
This article provides an insight into the creation of the Ambassador open source API gateway for Kubernetes, and discusses the technical challenges and lessons learned from building a developer-focused control plane for managing ingress or "edge" traffic within microservice-based applications.
Agent Gateway overview | Gemini Enterprise Agent Platform | Google Cloud Documentation
Secure and govern AI agent connectivity with Agent Gateway. Centralize access policies, mTLS, and Model Context Protocol (MCP) security for agent-to-agent and agent-to-tool interactions across diverse runtimes.
OpenAI Model Spec
The Model Spec specifies desired behavior for the models underlying OpenAI's products (including our APIs).
Pricing | OpenRouter
Transparent pricing for OpenRouter. Pay only for what you use with access to 400+ AI models. Free tier, Pay-as-you-go, and Enterprise plans available.
BerriAI/litellm
Python SDK, Proxy Server (AI Gateway) to call 100+ LLM APIs in OpenAI (or native) format, with cost tracking, guardrails, loadbalancing and logging. [Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, HuggingFace, VLLM, NVIDIA NIM]
Latency optimization | OpenAI API
Improve latency across a wide variety of LLM-related use cases.
Interactions API: A unified foundation for models and agents
Google’s Interactions API is a unified interface for interacting with Gemini models and agents.
freestylefly/wesight
Open-source desktop AI agent workspace with one-click Claude Code, Codex, OpenClaw, Hermes Agent setup and custom LLM model routing.
OpenAI to acquire Ona
OpenAI plans to acquire Ona to expand Codex with secure, persistent cloud environments, enabling long-running AI agents across enterprise workflows.
