# llm-optimization

> Browse 2 items tagged with llm-optimization.

## Items

- [CommVQ](https://vectordb.ever.works/items/commvq) — A commutative vector quantization method for KV cache compression that reduces FP16 cache size by 87.5% with 2-bit quantization and enables 1-bit quantization, allowing LLaMA-3.1 8B to run with 128K context on a single RTX 4090 GPU.
- [VQKV](https://vectordb.ever.works/items/vqkv) — A training-free vector quantization method for KV cache compression in Large Language Models that achieves 82.8% compression ratio on LLaMA3.1-8B while retaining 98.6% baseline performance and enabling 4.3x longer generation length on the same memory footprint.

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_Canonical page: https://vectordb.ever.works/tags/llm-optimization_