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Gavin Li
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[**Example notebooks**](#example-python-notebook) |
[**FAQ**](#faq)
**AirLLM** optimizes inference memory usage, allowing 70B large language models to run inference on a single 4GB GPU card. No quantization, distillation, pruning or other model compression techniques that would result in degraded model performance are needed. And you can run 405B Llama3.1 on 8GB vmem.
**AirLLM** optimizes inference memory usage, allowing 70B large language models to run inference on a single 4GB GPU card without quantization, distillation and pruning. And you can run 405B Llama3.1 on 8GB vmem now.
<a href="https://github.com/lyogavin/airllm/stargazers">![GitHub Repo stars](https://img.shields.io/github/stars/lyogavin/airllm?style=social)</a>
[![Downloads](https://static.pepy.tech/personalized-badge/airllm?period=total&units=international_system&left_color=grey&right_color=blue&left_text=downloads)](https://pepy.tech/project/airllm)