A timestamp can reduce Claude prompt-cache hits to zero if it appears before the cache breakpoint. Anthropic says the cache matches the prompt content up to that breakpoint, so a changing timestamp makes the prefix different on each request. Put stable shared context before the breakpoint and changing request data after it.
Why a timestamp can prevent Claude cache hits
Claude prompt caching reuses a matching prompt prefix. Anthropic describes the cache key as a cryptographic hash of the prompt content up to the cache-control breakpoint. If that prefix changes, the request no longer matches the existing cache entry.
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A timestamp placed inside that prefix changes from request to request. Anthropic specifically warns that placing a breakpoint on a block that changes every request, such as a timestamp or arbitrary user input, writes a fresh entry each time rather than producing cache reads. The mechanism can explain a 0% hit rate, though the documentation does not verify any particular user’s incident or measured rate.
Move changing content after the breakpoint
Structure the request so the cache boundary follows the material you reuse, not the values that change each call.
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- Before the breakpoint: repeated system instructions, tool definitions, and other stable shared context.
- After the breakpoint: timestamps, user-specific input, and other request-specific content.
Anthropic supports automatic caching, which adds a top-level cache_control and moves the breakpoint to the last cacheable block as a conversation grows. Explicit breakpoints provide finer placement control. Check the documentation for the applicable cacheable-token minimum for your platform and model: Anthropic’s prompt caching documentation.
Confirm cache reuse in the API response
Inspect the response’s usage fields across repeated requests. Anthropic documents these token counts in its Claude API prompt caching guide.
cache_read_input_tokenscounts tokens read from cache.cache_creation_input_tokenscounts tokens written to cache.input_tokensrepresents tokens after the last cache breakpoint. For total input processed, addcache_read_input_tokens,cache_creation_input_tokens, andinput_tokens.
A cache-read count on a repeated request is evidence of reuse. Latency alone does not establish that a cache hit occurred.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Account for cache pricing
Anthropic’s pricing documentation, accessed in 2026, lists these cache pricing multipliers relative to base input-token pricing. Dollar costs depend on the model; check the Anthropic pricing page for current rates.
Quick Recap
| Cache operation | Multiplier |
|---|---|
| 5-minute cache write | 1.25× base input-token price |
| 1-hour cache write | 2× base input-token price |
| Cache read | 0.1× base input-token price |
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
