120B in 8GB

·2026.04.13 04:53

Key point

LazyMoE aims for ultra-low-memory execution of a 120B LLM using lazy expert loading and TurboQuant.

LazyMoE combines lazy expert loading with TurboQuant to aim for running a 120B LLM in an 8GB RAM environment without a GPU.

The key points are as follows.

It lazily loads only the needed experts in large MoE models, reducing the memory burden.
TurboQuant further compresses the model weights, increasing feasibility of running on low-spec environments.
As a result, this is an approach that expands the scope of local execution of high-capacity LLMs.

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