5 Hidden Features of KTransformers in the 17K Star MoE Framework

你知道吗？2026 年中期，在生产环境部署 671B 参数的 DeepSeek-R1 仍然需要 8 张 H100，硬件成本约 20 万美元。但清华大学 MADSys 实验室的开源项目早在 2024 年就能在单台工作站上跑 236B 参数 MoE 模型，2025 年 2 月甚至在普通硬件上实现了 671B DeepSeek-R1 286 tokens/s 的 Prefill 速度。这个项目就是 kvcache-ai/ktransformers，截至 2026-06-12 已有 17,264 Stars、1,313 Forks、Apache-2.0 协议。2026 年的 AI 基础设施叙事被 NV

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AiFeed24 Team·⏱ 1 min read·News

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Tags:#cloud-computing #machine-learning #deep-learning #open-source #ai-models

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5 Hidden Features of KTransformers in the 17K Star MoE Framework

Deep Analysis

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5 Hidden Features of KTransformers in the 17K Star MoE Framework

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