AI Gateway Caching Explained — Why L1 + L2 Cache Layers Cut 90% of Your LLM Bill

TL;DR Caching in AI gateways is not one feature. It's two: L1 — Result cache skips the upstream model entirely. 100% savings per hit. L2 — Prompt cache (vendor-native) reduces cached input token cost 50-90%, but still calls the model. Most teams on OpenRouter, Portkey, or similar gateways get only L2. Adding L1 (Helicone or self-hosted Redis) compounds the savings. Real production math: a typical 10M request/month workload saves 39% with L2 alone, 54% with L1 + L2 stacked. Full analysis...