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KTransformers is a framework that optimizes inference and fine-tuning of large Mixture-of-Experts models by dynamically placing only active experts on the GPU while keeping the rest in CPU memory, enabling large models like DeepSeek-V3 to run on limited consumer GPU memory.
OpenInfer demonstrates "vertical disaggregation" that boosts Qwen 3.5 27B throughput by ~50% by co-executing quantized layers across a single node’s AMD EPYC CPU and Nvidia L40S GPU with a custom SLA-aware scheduler.