Awesome-LLM-Compression

Overview

Awesome-LLM-Compression is a community-maintained curated list of research papers and tools focused on compressing large language models. It organizes resources by techniques like pruning, quantization, knowledge distillation, and parameter sharing for easy reference.

Best for

Best for
Researchers and engineers exploring LLM compression for efficient deployment

Use cases

• Discovering state-of-the-art LLM compression methods and benchmarks
• Comparing different compression techniques for model deployment
• Staying updated on recent academic work and open-source tools

Notes

Awesome-LLM-Compression is a community-maintained curated list of research papers and tools focused on compressing large language models. It organizes resources by techniques like pruning, quantization, knowledge distillation, and parameter sharing for easy reference.

1,840 stars on GitHub. Last updated 2026-02-23. Licensed MIT.

Use cases

• Discovering state-of-the-art LLM compression methods and benchmarks
• Comparing different compression techniques for model deployment
• Staying updated on recent academic work and open-source tools

Pros

• Comprehensive collection of papers and tools in one place
• High community visibility with 1840 GitHub stars
• Free and open source, continuously updated

Cons

• Not a tool itself; requires manual evaluation of listed resources
• No built-in code or implementation for immediate use
• Quality of linked tools may vary without curation beyond listing

Indexed from awesome-llm and enriched against its public facts.