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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.
Yannick Nick demonstrates running DeepSeek V4 Flash with native FP4+FP8 precision on 2x RTX Pro 6000 GPUs using KTransformers, enabling efficient inference on resource-constrained systems.
A user reports successfully running the DeepSeek V4 Pro model locally using ktransformers and sharing detailed benchmark results across various context depths, demonstrating improved inference speeds.
KTransformers is a flexible research framework for cutting-edge LLM inference and fine-tuning, leveraging CPU-GPU heterogeneous computing and supporting many recent models.