When to Choose Each Option
Clear guidance based on your specific situation and needs.
Our Recommendation
Prompt caching wins clearly for high-repetition workloads with a large, stable prefix — agentic loops that re-send the same system prompt and tool definitions, long multi-turn chats, RAG over a fixed corpus, and batch runs of many variations against one context. There, cache reads at 10% of base input and up to 80% lower latency are decisive, and a warm cache costs nothing to keep alive within the TTL. Uncached calls win when prompts are short, diverse, or used only once or twice: the 25% write premium never amortizes, and you avoid all cache-boundary and TTL reasoning plus the messier three-way bill of writes, reads, and regular input. The honest rule of thumb: cache anything you send more than a couple of times inside the cache window, and skip it for genuinely one-shot or constantly-changing prompts. For teams staring down the Fable 5 cost cliff, caching a fixed prefix drops its repeated portion from $10 to roughly $1 per million tokens — which is exactly the kind of infrastructure-level optimization Context Studios builds into client agent systems by default.
- Choose Prompt Caching when...
- You re-send a large, stable prefix — system prompt, tool definitions, few-shot examples, or a fixed document — across many calls
- You run long multi-turn conversations that keep resending the earlier turns
- You do RAG over a fixed corpus and want the instructions or retrieved context cached between queries
- You fire many prompt variations (evals, A/B tests, batch jobs) against the same context within a short window
- Choose Uncached API Calls when...
- Your prompts are short (below OpenAI's 1,024-token cache threshold) or highly diverse from call to call
- Each context is used only once or twice, so the cache-write premium never pays back
- The context changes on every request, leaving nothing stable worth caching
- You want the simplest possible billing with no TTL, cache boundary, or staleness window to manage