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vLLM Dynamic Expert Caching for Low-VRAM MoE

A new PR in vLLM introduces dynamic expert caching with LRU policy, enabling 16G MoE models on 8G VRAM by keeping active experts in VRAM and offloading others to RAM. On cache misses, computation shifts to CPU while reshuffling experts to minimize latency. Upcoming features include mxfp4 quantization and disk streaming.

Reddit r/LocalLLaMACommunityMar 17#expert-caching#moe-inference#low-vram