Should You Use Prompt Caching? (Anthropic + OpenAI)
Use prompt caching if you have a system prompt over 1,024 tokens that's sent on most requests, or if you load the same documents into context repeatedly. At 1,000+ requests/day with a 50K token system prompt, caching typically saves $300–1,500/month with Claude Sonnet 4.
Do you have content that stays the same across most requests?
FAQ
How do I implement prompt caching with Anthropic?+
Add `cache_control: {type: 'ephemeral'}` to the content blocks you want to cache in your messages array. Place these blocks before the variable user content. The cache key is based on the exact text of the prefix — any change invalidates the cache. The default cache duration is 5 minutes; use Anthropic's extended caching (beta) for 1-hour TTL on frequently accessed prompts.
How do I implement prompt caching with OpenAI?+
You don't need to do anything — OpenAI applies automatic prompt caching to any request with a prefix over 1,024 tokens. The key is structuring your prompts correctly: put all stable content (system prompt, documents, examples) at the beginning of your messages array, and variable content (user query) at the end. Check the usage object in API responses for 'prompt_tokens_details.cached_tokens' to verify cache hits.
What is the cache hit rate I should target?+
Target over 70% cache hit rate for positive ROI with Anthropic caching (which has a cache write surcharge). With OpenAI's automatic caching (no surcharge), any hit rate above 0% is beneficial. Cache hit rate depends on request frequency relative to the 5-minute (Anthropic) or session-based (OpenAI) cache TTL. High-traffic applications with stable prompts typically achieve 85–95% cache hit rates.
Does prompt caching affect response quality?+
No. Prompt caching is transparent to the model — cached tokens produce exactly the same results as uncached tokens. The model processes cached tokens from its KV cache rather than re-computing them, but the computation over those tokens is identical. There is no quality tradeoff, only a cost and latency benefit (cached requests are typically 10–30% faster to first token).