AI Gateway

An AI gateway is the control layer between your applications and every LLM provider, self-hosted model, and MCP server they call. This guide compares the five types of AI gateway, matches each to team situations, and lays out a proof of concept to test a shortlist.

AI gateways sit between coding agents and model providers so platform teams can issue per-developer keys, cap spend, and switch models centrally. This guide compares Bifrost, LiteLLM, Vercel AI Gateway, OpenRouter, and Kong AI Gateway for Claude Code, Codex CLI, and Cursor traffic.

AI gateways for multimodal workloads route images, audio, embeddings, and batch jobs through one governed API. This guide compares Bifrost, LiteLLM, Kong AI Gateway, Cloudflare AI Gateway, and Vercel AI Gateway on the request types each one supports.

An AI gateway gives self-hosted inference servers and cloud LLM providers one API, one routing layer, and one place to enforce policy. This guide compares Bifrost, LiteLLM, Kong AI Gateway, Envoy AI Gateway, and Cloudflare AI Gateway for hybrid vLLM, Ollama, and cloud deployments.

An AI gateway is the control plane between your applications, agents, and every model provider they call. This guide ranks the best AI gateway approaches for 2026, from the Bifrost open-source control plane to managed platform gateways and API platform extensions.

Prompt caching lets an LLM provider reuse the computation for a repeated prompt prefix, cutting input cost and time to first token. This guide covers provider differences, prompt structure, cost trade-offs, and how to automate cache markers at the gateway.