Context Caching
Context caching is an optimization technique where AI providers store and reuse previously processed prompt prefixes across multiple API calls. When you send the same system prompt, few-shot examples, or reference documents repeatedly, context caching avoids re-processing those tokens, reducing latency and cost. This is particularly valuable for applications that use long, static system prompts or large reference documents.
Example
You build a customer support bot with a 10,000-token system prompt containing product documentation. Without context caching, every customer query re-processes those 10,000 tokens. With caching, the system prompt is processed once and reused across all subsequent queries — cutting response time and API costs significantly.
Put this into practice
Build polished, copy-ready prompts in under 60 seconds with SurePrompts.
Try SurePrompts