Exact match misses most of the repeat traffic
Exact-match caching only catches requests that are byte-for-byte identical, but a large share of repeat traffic is semantically identical: the same question asked in different words, or the same classification with different phrasing. Without semantic caching, that traffic re-runs the full model every time, driving up latency and provider token spend.
- Byte-identical caching misses the larger population of near-duplicate requests
- Identical user intents worded slightly differently incur full model latency and cost
- Wrong-answer risk from serving a semantically 'close enough' response with no safety gate
- Risk of unverified or low-fidelity vector representations serving cached responses