Posts tagged with "Prompt Caching"

Claude Fable 5.1 keeps Fable 5's $10/$50 pricing but cuts cache reads to $0.25 per million tokens, which turns a 60-turn agent session from $17.25 into $10.50 and shrinks the premium over Opus 5 from 2x to about 22%. On Microsoft Foundry it ships Anthropic-hosted only, with no EU data zone, no Batches API, a zero default quota on pay-as-you-go, mandatory 30-day retention until Enterprise Frontier Safeguards arrive, and three breaking changes for teams migrating from Fable 5.

Anthropic prices prompt caching with three numbers: a 1.25x or 2x premium on cache writes depending on TTL, a 0.1x rate on cache reads, and the base input rate for everything after the last breakpoint. This deep-dive verifies every figure against the current official docs and covers per-model minimums, break-even math, batch stacking and how Claude on Azure converts it all into CCUs.

Claude Opus 4.8 arrives at unchanged pricing with an effort control on all plans, a fast mode at a third of the previous fast-inference cost, and a Messages API change that lets system entries sit inside the messages array so mid-task instruction updates no longer invalidate the prompt cache. Worked token math shows cache hit rate remains the biggest cost lever, and a four-question framework matches effort, speed and fan-out to each workload.

Prompt caching is the highest-ROI cost lever on long-context LLM workloads in 2026. Anthropic, OpenAI, and Azure OpenAI all offer it with different pricing and breakpoint semantics. A worked comparison of the three providers, the placement patterns that actually hit cache, where the cache silently goes cold, and a 30-minute audit that pays back.

A technical guide to prompt caching across Claude, Azure OpenAI, and GPT — what belongs in the cache, how to structure cache breakpoints, TTL realities, hit-rate optimization, and the anti-patterns that erase the savings.