Anthropic Prompt Caching — Cut AI API Costs 90%

What is Prompt Caching?

Prompt caching lets you cache frequently reused content (system prompts, tool definitions, large documents) across API requests. Instead of re-processing the same tokens every time, Claude reads them from cache at 1/10th the cost. For applications with long system prompts or RAG context, this can reduce costs by 90%.

Answer-Ready: Anthropic's prompt caching reduces Claude API costs up to 90%. Cache system prompts, tool definitions, and documents across requests. Cached tokens cost 1/10th of input tokens. 5-minute TTL, auto-extended on hit. Essential for production AI applications with recurring context.

Best for: Teams running Claude API at scale with recurring system prompts. Works with: Claude Sonnet, Opus, Haiku via Anthropic API. Setup time: Add one field to existing code.

How It Works

Pricing Impact

Cache TTL

• Default: 5 minutes
• Auto-extended: Each cache hit resets the 5-minute timer
• Minimum cacheable: 1,024 tokens (Sonnet), 2,048 tokens (Opus)

Cacheable Content

1. System Prompts

system=[{
    "type": "text",
    "text": "Your 2000-token system prompt here...",
    "cache_control": {"type": "ephemeral"},
}]

2. Tool Definitions

tools = [
    {"name": "search", "description": "...", "input_schema": {...},
     "cache_control": {"type": "ephemeral"}},
]

3. Long Documents (RAG Context)

messages = [
    {"role": "user", "content": [
        {"type": "text", "text": "Here is the full codebase:\n" + large_document,
         "cache_control": {"type": "ephemeral"}},
        {"type": "text", "text": "Now answer: what does the auth module do?"},
    ]},
]

4. Multi-Turn with Cached Prefix

# Turn 1: Cache the document
msg1 = {"role": "user", "content": [
    {"type": "text", "text": document, "cache_control": {"type": "ephemeral"}},
    {"type": "text", "text": "Summarize this document"},
]}

# Turn 2: Document is already cached, only new question costs full price
msg2 = {"role": "user", "content": "Now list the key findings"}

Cost Calculator

Best Practices

1. Cache the longest, most stable content first — System prompts and tool definitions change rarely
2. Order matters — Cached content must be a prefix. Put cached content before dynamic content
3. Monitor cache hits — Check usage.cache_creation_input_tokens and usage.cache_read_input_tokens in response
4. Minimum size — Content must be >= 1,024 tokens to be cacheable
5. Keep cache warm — If requests are >5 minutes apart, cache expires

FAQ

Q: Does caching affect response quality? A: No. Caching is purely an optimization — the model sees identical input.

Q: Can I cache across different conversations? A: Yes, if the cached prefix is identical (same system prompt + tools), it hits the cache regardless of the user message.

Q: Does Claude Code use prompt caching? A: Yes, Claude Code automatically uses prompt caching for CLAUDE.md content, tool definitions, and conversation history.