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lyogavin/airllm
AirLLM 2.8T LLM inference with single 4GB GPU
Brief / README 摘要
查看原文*Quickstart | *Configurations | *MacOS | *Example notebooks | *FAQ** *AirLLM dramatically reduces inference memory usage, letting 70B large language models run on a single 4GB GPU card — without quantization, distillation, or pruning. You can even run Kimi K3 (2.8T) — the largest open-source model released to date — on under 4GB, Qwen3.8-Flash-Next (125B) on 6GB, and DeepSeek-V3 (671B) on ~12GB. We now also support training huge models on small VRAM: Qwen3.8-Flash-Next (125B) under 6GB**. Best AI Game Sprite Generator Best AI Facial Expression Editor [2026/09] Training support: stream frozen w…
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