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[GitHub Trending] lyogavin/airllm

8.2 relevance
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AirLLM enables large model inference on low-end GPUs, highly relevant and trending.

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

AirLLM enables inference of massive open-source LLMs on consumer GPUs by streaming model layers and MoE experts one at a time, avoiding quantization or pruning. It runs 70B models on 4GB, 405B Llama 3.1 on 8GB, DeepSeek-V3 (671B) on ~12GB, and the 2.8T-parameter Kimi K3 on under 4GB of VRAM. The library provides a single AutoModel API compatible with Qwen, Llama, DeepSeek, and other popular architectures.

Author

lyogavin