Semantic caching: how it works, and where it breaks
A semantic cache reuses an old answer when a new question is similar enough. That single idea has a few sharp edges — a similarity score isn't a correctness check, the threshold that governs it is hard to set, and it's easy to confuse with the unrelated thing your model provider calls caching. These guides walk through each one, with what's measured and what's still open.
Concepts
ConceptWhen a semantic cache serves the wrong answerA similarity score says two questions look alike — not that an old answer is still correct for a new one. The gray zone, a false-positive taxonomy checked against real traffic, and what happens when an agent trusts a bad hit.Read How-toHow semantic cache similarity thresholds workτ_low, τ_high, and the gray zone between them. How to set the cutoff by sweeping your own traffic — and the measured ceiling on how far tuning it alone gets you.Read DisambiguationPrompt caching vs semantic cachingThey get searched interchangeably and solve different problems. One is a provider-side discount for an exact prompt prefix; the other reuses an answer across differently-worded requests — and only that one can be wrong.Read
Comparisons
ComparisonCacheVerifier vs Redis LangCacheLangCache is a managed semantic cache. CacheVerifier is a correctness check on the hits it serves. Where the line sits, and when you'd want both.Read ComparisonCacheVerifier vs vCachevCache learns a per-prompt threshold with a formal error bound — you adopt it as your cache. CacheVerifier keeps the cache you run and adds a verification step.Read ComparisonGPTCache + a verification layerGPTCache's SimilarityEvaluation hook is where a wrong hit slips through — or gets caught. CacheVerifier drops straight into it, no fork.Read
The measured results
The guides above draw on our own research: how much label noise fine-tuning tolerates, how little data it needs, whether the gain holds up over time, whether verification actually beats raising the threshold, and the one production dataset where it broke — checked across three public benchmarks and real support traffic.