郭明𫓹：DeepSeek爆红将加速端侧AI发展_老虎社区_美港股上老虎

郭明𫓹：DeepSeek爆红将加速端侧AI发展

IT之家2025-02-05

IT之家 2 月 5 日消息，天风国际分析师郭明𫓹于 5 日发文称，DeepSeek 爆红后，端侧 AI 的发展速度加快。DeepSeek 的流行直接推动了英伟达 H100 训练需求的增长，表明优化的训练方法（可有效降低成本）能够刺激市场，同时也再次证明了 CUDA 生态的竞争力（用户为何选择 H100）。IT之家附郭明𫓹分析大意如下：台积电和英伟达预计，到 2026 年，端侧 AI（on-...

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AI（on-device AI）将迎来快速增长。台积电在财报电话会议上提到，2026 年端侧 AI 发展将更加明显，而英伟达计划在 2025 年第四季度至 2026 年上半年量产其 AI PC 芯片 N1X / N1。DeepSeek 爆红后，端侧 AI 的发展速度加快。DeepSeek 的流行直接推动了英伟达 H100 训练需求的增长，表明优化的训练方法（可有效降低成本）能够刺激市场，同时也再次证明了 CUDA 生态的竞争力（用户为何选择 H100）。更值得关注的是，DeepSeek 带动了本地大模型（LLM）部署的热潮。DeepSeek R1 通过优化训练方法，提升了本地设备上中小规模 LLM 的性能，而用户对云端 DeepSeek 服务的数据安全担忧也加速了这一趋势。预计未来将有更多类似 DeepSeek 的开源模型问世，进一步推动本地 LLM 生态的发展。目前，常见的本地 DeepSeek 部署方式包括：使用 LM Studio 进行便捷部署，Ollama 运行模型，4-bit / 8-bit 量化降低显存需求同时保持性能，模型规模覆盖 15 亿到 700 亿参数，硬件范围从低端笔记本到搭载英伟达独立 GPU 的高端 PC。目前，本地 DeepSeek 部署仍处于小众市场，对英伟达云端 AI 芯片的需求影响不大。但从长期来看，尽管终端计算会部分替代云计算，它同样可能带来新的云端需求（类似 H100）。端侧 AI 和云端计算预计将同步增长，并最终形成一个融合的 AI 生态系统。尽管长期来看云计算增长仍具潜力，但端侧 AI 发展速度超出预期，可能会导致云计算增速短期内低于市场预期，并影响投资情绪。未来，可能减少云计算增长不确定性的因素包括 GB200 NVL72 量产成功带动计算规模扩展，以及 AI 在机器人、自动驾驶和多模态领域的商业化进展逐步明朗。就台积电和英伟达而言，台积电仍是端侧 AI 发展的主要受益者（受益于芯片升级），而英伟达在端侧 AI 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