Best AI Gateways for Claude Opus 4.7

Vercel AI Gateway is a centralized AI model routing and infrastructure platform designed to help developers build, deploy, and scale AI-powered applications using a single unified interface for multiple AI providers and models. The platform enables developers to access text, image, and video generation models from leading AI labs including OpenAI, Anthropic, xAI, and other providers through one API endpoint, one authentication layer, and one management dashboard. AI Gateway simplifies AI application development by consolidating model routing, usage monitoring, billing, failover management, and observability into a single system, eliminating the need to integrate separately with multiple AI vendors. Developers can use the Vercel AI SDK or OpenAI-compatible APIs to build AI applications with support for streaming responses, stateful agents, multimodal generation, tool calling, and conversational workflows. The platform includes built-in resiliency features such as automatic provider failovers and workload routing to maintain uptime during outages or degraded model performance. AI Gateway also provides unified cost tracking and transparent billing with no markup over provider pricing, helping teams monitor AI usage across applications and providers more effectively. In addition to text generation, the platform supports image generation and editing workflows, as well as production-ready AI video generation capabilities accessible through prompt-based interfaces. Integrated developer tooling, SDKs for multiple programming languages, authentication management, and deployment workflows make Vercel AI Gateway particularly suited for modern web applications, AI agents, SaaS platforms, and developer-focused AI products.

Cloudflare AI Gateway serves as an advanced control plane for AI applications, designed to seamlessly connect to various models while dynamically managing request routing, usage tracking, billing, and logging through a single, cohesive interface. This platform empowers teams by providing enhanced visibility and oversight of their AI applications, enabling them to analyze user interactions through detailed analytics and logs, as well as efficiently manage application scalability through features like caching, rate limiting, request retries, and model fallback. By utilizing response caching and minimizing redundant API calls, AI Gateway effectively lowers costs and reduces latency, allowing frequent requests to be fulfilled directly from Cloudflare’s cache rather than relying on the original model provider. Additionally, it boosts reliability with adaptable controls that determine the timing and conditions under which model provider APIs are accessed, guided by various factors such as attributes, fallbacks, latency, cost, and availability. Importantly, routing rules can be modified directly from the dashboard or via API calls without necessitating redeployments or causing any service interruptions, ensuring a smooth operational experience. In this way, organizations can optimize their AI app performance while maintaining flexibility and control.

Cheaper Inference serves as an API gateway compatible with OpenAI, enabling users to access various AI models from different providers through a unified API key, thus eliminating the need for any changes in request formatting. Developers have the flexibility to switch providers simply by updating the base URL and API key while retaining the same model, messages, tools, streaming configurations, and response management. This service accommodates both text and image models, facilitates vision-enabled chat requests, offers streaming capabilities, includes prompt caching, provides reasoning controls, and allows temporary image uploads for more extensive vision data. Each request can have its model selected individually, and users can filter the catalog based on model type, vision capabilities, reasoning options, streaming availability, or provider identity. The system includes automatic retries to manage network disruptions and provider errors, with fallback routes available for eligible requests to prevent failures. Additionally, every request is documented in the History section, allowing teams to track request volume, token consumption, and overall operational activity, ensuring comprehensive oversight and management of AI interactions. This transparency assists in optimizing usage and understanding patterns over time.