Token caching can cut enterprise AI costs by 80%

In 2026, the biggest cost advantage isn’t choosing a cheaper model — it’s token caching.

When the same system prompts or knowledge base get reused, providers discount that input by 80–90%. Claude Sonnet 5, for example, drops from $2.00 to $0.20 per million tokens on cached content.

Enterprises with heavy RAG or multi-turn workflows are leaving $400K–$520K on the table annually by not using it.

Key takeaway for procurement:

Stop comparing raw token prices. Start modeling cost-per-result on your actual query patterns. Smaller models with strong caching often win.

Full analysis:

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Stop overpaying for AI APIs. Learn how token caching slashes RAG and LLM costs by 80% to lower your corporate cost-per-result.