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lyogavin

lyogavin/airllm

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2026-08-06
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Project Intro

使用单张4GB GPU实现AirLLM 70B推理

AirLLM 70B inference with single 4GB GPU

AI Interpretation

AI Interpretation Auto generated

AirLLM大幅降低大模型推理内存占用，让70B参数模型可运行在单张4GB GPU上，无需量化、蒸馏或剪枝。通过稀疏MoE逐专家流式加载机制，还能运行405B Llama 3.1、DeepSeek-V3（671B）甚至2.8T参数的Kimi K3模型，显存占用分别仅需8GB、12GB和不到4GB。支持FP8量化及Qwen3、Llama等主流开源模型，适合资源有限的个人开发者进行大模型推理和微调实验。

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Project Health Score

A
87/100
优秀
ActivityPopularityGrowthCommunityDocs
Activity 23/23

1 days since last update

Popularity 25/25

Platform Star TOP 2% · Forks 3,162

Growth 23/25

This week +1,588 ⭐ · This month +3,621 ⭐

Community 7/17

9 contributors · 0 platform comments

Docs 9/10

1 item(s) missing

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Project Info

Author lyogavin
Source GitHub
Period Daily
Repo Id lyogavin/airllm
Latest Commit 2026-08-06 08:40:04
First Collected 2026-08-05 08:00:54
Last Updated 2026-08-07 08:00:32

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