Context Caching

Definition

Context caching stores intermediate computations for repeated or similar prompts, reducing cost and latency.

How It Works: - Cache key-value representations - Reuse for similar/repeated prompts - Only compute new/changed parts - Significant cost savings

Implementations: - Anthropic Prompt Caching - KV cache in inference - Prefix caching

Benefits: - 50-90% cost reduction for long contexts - Faster responses - Better for repeated queries - Efficient RAG applications

Use Cases: - Long system prompts - Document Q&A - Multi-turn conversations - RAG with fixed context

Considerations: - Cache invalidation - Memory requirements - Not all providers support

Caching a long document to answer multiple questions about it cheaply.

Using a trained AI model to make predictions on new, unseen data.

The maximum amount of text a language model can process at once.