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I run 30B 22tok/s, 109tok/s not novel,6GB/16GB RAM overcoming llama.cpp

在低资源设备（6GB/16GB RAM）上高效运行大模型（如30B参数、22tok/s推理速度），通过优化llama.cpp实现高性能推理，适合本地部署AI模型的开发者和研究者
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为什么值得关注

突破硬件限制实现大模型本地运行，满足对隐私、成本敏感的AI应用需求，是轻量化大模型落地的重要实践

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