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English(EN) Lawyer with too many GPUs, part 3: DeepSeek-V4.1-Flash on 2x DGX Spark + an old 3090 box. 2,600+ tok/s prefill to 256K, 322 tok/s structured output, full stack and raw data published

DeepSeek-V4.1-Flash在2台DGX Spark上实现2,600+ tok/s预填充

作者 PulseAugur 编辑部 · [1 个来源] ·

一位经营PLI Labs的律师发布了DeepSeek-V4.1-Flash模型的性能基准测试，该测试使用了复杂的硬件设置。该配置包括两台DGX Spark服务器用于模型，以及一台带有两块3090 GPU的独立机器用于推测性起草和Engram表卸载。该设置在256K上下文上实现了超过2,600 tokens/s的预填充速度，以及322 tokens/s的结构化输出速度，完整的堆栈代码和原始数据已公开提供。 AI

影响 为特定模型和硬件配置提供了详细的性能数据，有助于优化推理的运营商。

排序理由 发布了开源模型的性能基准测试和技术细节。[lever_c_demoted from research: ic=1 ai=1.0]

在 r/LocalLLaMA 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

DeepSeek-V4.1-Flash在2台DGX Spark上实现2,600+ tok/s预填充

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发布了开源模型的性能基准测试和技术细节。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/TumbleweedNew6515 ·

    GPU太多的律师，第三部分：DeepSeek-V4.1-Flash 在 2x DGX Spark + 一个旧的 3090 盒子上运行。2,600+ tok/s 预填充至 256K，322 tok/s 结构化输出，完整堆栈和原始数据已发布

    <!-- SC_OFF --><div class="md"><p>Update from the lawyer with the V100 server. I went and got two DGX Sparks, because of course I did. The mid-life crisis remains on schedule.</p> <p>Same deal as before: still a lawyer, still driving the whole thing through Claude Code, and Claud…

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