6 AI Gateways Compared for 2026: Routing, Governance, Caching, and Observability

Short summary

This post compares six AI gateways across provider coverage, governance, caching, cost visibility, audit logging, and observability. Gateways split into two camps: infrastructure-first platforms that extend existing API management or Kubernetes setups, and LLM-native gateways built specifically for model routing and prompt traffic. The key differentiator most comparisons miss is whether production observability data can feed evaluation workflows, not just populate dashboards.

• •Six AI gateways compared on provider coverage, governance, caching, cost tracking, audit logging, and observability
• •Two camps: infrastructure-first (extends existing API/K8s platforms) vs LLM-native (built for model routing and prompt traffic)
• •Key differentiator: whether gateway observability data can become evaluation cases, scorers, or release checks — not just dashboard rows

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