A production-focused guide comparing prompt caching implementations across Anthropic (Claude), OpenAI, and Gemini in 2026. Covers pricing models, TTLs, and key differences: Anthropic offers explicit cache_control breakpoints with 90% read discounts but 5-minute TTLs; OpenAI provides automatic caching with 50% discounts and no configuration; Gemini supports long TTLs up to 24 hours with per-hour storage billing. Includes real cost numbers from a 50k requests/day support bot showing 85% cost reduction, common hit-rate failure patterns (multi-tenancy, TTL mismatches, silent invalidation from prompt changes), and structural rules for designing cacheable prompts. Recommends choosing caching strategy per feature rather than per provider.
Table of contents
Why Caching Became The Whole Ball GameHow Each Provider Actually Implements ItThe Hit Rate TrapThe Structural Rules That Actually WorkA Real Example: A Support Bot At 50k Requests Per DayWhen Caching Will Not Help YouThe Multi-Provider Strategy That WorksWhat To Do Monday MorningSort: