AirLLM Runs 70B LLMs on a Single 4GB GPU
AirLLM 70B inference with single 4GB GPU
AirLLM slashes inference memory usage, enabling 70B models to run on a single 4GB GPU without quantization, distillation, or pruning. It streams one layer at a time, so VRAM needs depend on layer size, not total model size. This lets you run Llama 3.1 405B on 8GB, DeepSeek-V3 671B on ~12GB, and even Kimi K3 2.8T on under 4GB. The library supports virtually every popular open LLM via AutoModel, with optional 4-bit/8-bit compression for up to 3x speedup.
AirLLM dramatically reduces inference memory usage, letting 70B large language models run on a single 4GB GPU card — without quantization, distillation, or pruning.