Best 3 Types of Caching in LLMs with Codes

In the world of large language models (LLMs), optimizing performance isn’t just a luxury — it’s a necessity. As the demand for faster responses and cost-effective AI solutions grows, caching strategies have emerged as powerful tools to streamline LLM operations.

This article dives into the different types of caching techniques — ranging from rapid in-memory methods to persistent disk-based approaches and the more sophisticated semantic caching. Discover how each method not only accelerates response times but also minimizes costs, and learn how to leverage these techniques for a smarter, more efficient LLM deployment.

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What is caching?

1. Store and reuse responses.
2. Improve response time.
3. Reduce cost.

Types of Caching

1. In-memory caching.
2. Disk-based caching.
3. Semantic caching.