Project Overview
LMCache is an open-source KV cache layer designed to improve the performance of LLM services by reusing attention states. It enables KV cache reuse across requests and engines, reducing redundant computation and lowering first-token latency, especially for long-context and RAG workloads.
Core Features
- Reuse KV cache across requests: Share attention states between requests to avoid repeated computation.
- Compatibility across engines: Supports multiple inference engines, facilishing integration into existing systems.
- Reduced first-token latency: Speeds up response time via cache reuse.
Tech Stack and License
The project is primarily written in Python and follows the Apache-2.0 license. As of collection time, it has 10,183 stars on GitHub.
Getting Started
According to the README, users can start by cloning the repository and installing dependencies. For detailed installation and configuration steps, please refer to the project documentation.










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