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KTransformers enables efficient local inference for 1T-class MoE models on consumer hardware by leveraging CPU-GPU heterogeneous computing. It supports a full fine-tuning-to-inference loop, allowing model serving, feedback collection, and deployment back to the system. This approach makes large-scale model iteration accessible to small teams and researchers without high hardware costs.