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[GitHub Trending] lyogavin/airllm

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Enables LLM inference on limited hardware, highly relevant and innovative.

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

AirLLM is an open-source Python library that enables running massive LLMs—like 70B models on a 4GB GPU and even Kimi K3 (2.8T) on 3.72GB—by streaming layers or per-expert weights instead of loading the entire model, without quantization, distillation, or pruning. Its v3.0 adds FP8 support and one-line AutoModel inference for DeepSeek-V3 (671B on ~12GB) and Qwen3-235B (on ~3GB), while the latest update supports the largest open-source model, Kimi K3, via expert streaming on a single RTX 6000 Ada.

Author

lyogavin