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Anthropic and Google now support prompt caching, where large repeated system prompts or document contexts are cached server-side. Subsequent calls with the same cached prefix cost as little as 10% of normal input price. For RAG pipelines reusing the same document chunks, this is transformative.

Your system prompt is sent with every API request and billed as input tokens every time. A 2,000-token system prompt on 100,000 daily calls equals 200M tokens/day just in system prompts. Keep system prompts concise, or use prompt caching to amortize the cost.

Use cached input pricing when available — repeated system prompts can save 50%+ on input costs.

Implement caching strategies for repeated queries to reduce API calls and costs.

Beyond exact-match caching, consider semantic caching. If a new prompt is semantically similar to a previously cached one, you might be able to reuse the old response, potentially saving an API call.