Semantic Caching: Faster Responses, Lower Bills

LLM applications repeat themselves more often than we admit. Support macros, doc search, agent tool loops, and "what is our refund policy?" all generate near-duplicate prompts. Exact-match caching helps, but users rarely type the same string twice.

Semantic caching matches on meaning: if a new prompt is close enough to a cached request, Yaha returns the stored response without another provider round trip.

Exact cache vs semantic cache

| Approach | Hits when | Misses when | |----------|-----------|-------------| | Exact | Byte-identical prompt | Wording changes, extra whitespace | | Semantic | Paraphrases, minor edits | Truly new questions |

Semantic hits cut latency and provider cost simultaneously, often the difference between a snappy UX and a bill that scales linearly with traffic.

Where caching pays off

Teams see the biggest wins in:

• Customer support: FAQs and policy answers repeat across sessions
• Internal copilots: "how do I deploy X?" asked dozens of ways
• RAG pipelines: similar retrieval queries in batch jobs
• Multi-modal flows: repeated image or audio prompts in testing

Yaha's cache is gateway-native: any client using the OpenAI-compatible API benefits without embedding cache logic in each app.

Privacy and control

Caching is opt-in per project. You choose how long entries live, how closely prompts need to match, and which traffic uses the cache. Sensitive workloads can disable caching entirely while public-facing bots enable it aggressively.

Cached entries stay within your organization, never shared across tenants.

Measuring impact

The console shows cache hit rate alongside request volume and spend. A rising hit rate with steady answer quality usually means caching is helping. Sudden drops often mean prompts changed upstream, a cue to refresh or clear the cache.

Try it on your traffic

Enable semantic caching in Projects → Intelligence, route requests through the gateway, and watch hit rate over a few days of real usage. Start with stricter matching, then loosen as you validate answer quality.

curl https://gateway.yahagateway.io/v1/chat/completions \
  -H "Authorization: Bearer yaha.your-project-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4o-mini",
    "messages": [{"role": "user", "content": "What are your support hours?"}]
  }'

Send the same question with different phrasing on the second call. If caching is enabled and similarity matches, you will see lower latency on the hit.

Caching will not fix a bad prompt library, but it will stop you from paying twice for the same answer. That is low-effort savings worth turning on early.

Enable caching in your project: Sign in to the console.