Anthropic introduces the new Claude Prompt Caching feature, significantly enhancing AI conversation efficiency and cost-effectiveness. This article explores the use cases, benefits, and pricing strategies of this new feature, helping you fully leverage Claude’s powerful potential.
Prompt Caching is the latest feature of the Anthropic API, enabling developers to cache frequently used context between multiple API calls. With this technology, users can provide Claude with richer background knowledge and example outputs while dramatically reducing the cost (by up to 90%) and latency (by up to 85%) of long prompts.
This feature is currently in public testing on Claude 3.5 Sonnet and Claude 3 Haiku, with support for Claude 3 Opus coming soon.
Prompt Caching is particularly effective in the following scenarios:
Conversational Agents: Reduces the cost and latency of long conversations, especially those involving lengthy commands or document uploads.
Code Assistants: Improves autocomplete and code Q&A functions by retaining a summary version of the codebase in the prompt.
Large Document Processing: Allows complete long-form data (including images) to be included in prompts without increasing response latency.
Detailed Instruction Sets: Share extensive instructions, procedures, and examples to fine-tune Claude’s responses. Developers can now include dozens of diverse, high-quality example outputs to further enhance performance.
Agent Search and Tool Usage: Enhances the efficiency of multi-step tool calls and iterative changes, where each step typically requires a new API call.
Interacting with Books, Papers, and Other Long-Form Content: Embed entire documents in prompts, allowing users to interact with any knowledge base.
Early users have reported significant improvements in speed and cost across various use cases:
| Use Case | Uncached Latency (First Token Time) | Cached Latency (First Token Time) | Cost Reduction |
|---|---|---|---|
| Conversing with Books (100K-word cached prompt) | 11.5 seconds | 2.4 seconds (-79%) | -90% |
| Multi-Example Prompts (10K-word prompt) | 1.6 seconds | 1.1 seconds (-31%) | -86% |
| Multi-Turn Conversations (10 turns with long system prompt) | ~10 seconds | ~2.5 seconds (-75%) | -53% |
Prompt Caching pricing is based on the number of input tokens cached and the frequency of use:
[Prompt Caching for Claude 3 Opus is coming soon]
Notion is integrating the Prompt Caching feature into its Claude-powered Notion AI. By reducing costs and improving speed, Notion can optimize internal operations, creating a more advanced and responsive user experience.
Notion co-founder Simon Last said, “We’re excited to use Prompt Caching to make Notion AI faster, cheaper, and still maintain state-of-the-art quality.”
To start using the public beta of Prompt Caching on the Anthropic API, visit our documentation and pricing page.
Q: How does Prompt Caching affect API usage costs?
A: Prompt Caching can significantly reduce API usage costs, especially for applications requiring extensive context. Depending on the use case, costs can be reduced by up to 90%.
Q: Which Claude models support Prompt Caching?
A: Prompt Caching is currently supported on Claude 3.5 Sonnet and Claude 3 Haiku, with support for Claude 3 Opus coming soon.
Q: How do I implement Prompt Caching in my application?
A: You can implement Prompt Caching through the Anthropic API. Detailed implementation guides can be found in Anthropic’s official documentation.
Q: What are the privacy and security implications of Prompt Caching?
A: Anthropic implements strict security measures for cached content. The cached data is used solely to improve performance and is not repurposed for other uses.
Q: How much performance improvement can be expected with Prompt Caching?
A: Performance improvements vary by use case, but some users have reported latency reductions of up to 85%, particularly for long prompts and multi-turn conversations.
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