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[GitHub Trending] lyogavin/airllm

7.5 relevance
Score Breakdown
technical depth
8
novelty
8
actionability
7
community
6
strategic
6
personal
9

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Efficient 70B LLM inference on limited GPU, technically impressive and actionable.

AI/ML github.com
AirLLM 70B inference with single 4GB GPU. Contribute to lyogavin/airllm development by creating an account on GitHub.
Summary

AirLLM (lyogavin/airllm) slashes inference memory to run 70B models on 4GB GPUs and 405B Llama 3.1 on 8GB, all without quantization or pruning. Its v3.0 adds FP8 support and AutoModel for one-line loading of DeepSeek-V3 (671B on ~12GB) and Qwen3-235B (~3GB), plus block-wise quantization compression for 3x speedup with minimal accuracy loss.

Author

lyogavin