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开源了一个 1600 行的大模型推理引擎,能跑真实模型,测试场景吞吐超过 vLLM 想入门大模型推理,直接读 vLLM 太重。所以开源了 LiteMoE:约 1600 行 Python ,能跑真实的 Granite 模型,一个下午能读完主线。 适合想快速上手推理的同学: - 交互演示,逐步看一次真实推理: zhulinsen.github.io - 教程,从 KV Cache 、MoE 讲到 DeepSeek 、Kimi 、Qwen 的新设计: github.com/ZhuLinsen/LiteMoE/blob/main/docs/tutor… 固定批次的测试场景下,吞吐是 vLLM 的 105 ~ 109%,脚本可复现。算子用的是 vLLM 的,提升来自算子外的执行层。定位是学习和实验,上线还是用 vLLM 。 如果大家感兴趣,后面会继续做多卡、CPU 版本系列。 项目: ZhuLinsen/LiteMoE 演示: zhulinsen.github.io