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English(EN) Deepseek V4 flash performance on DGX Spark

Deepseek V4 Flash 在 DGX Spark 上实现 100 万上下文

一位用户已成功在 DGX Spark 系统上配置了 Deepseek V4 Flash,在 KV 缓存中实现了 100 万个 token 的最大上下文窗口。性能测试显示,在各种上下文长度下吞吐量保持一致,但在 32k token 时出现了一个显著的异常。用户报告称,Deepseek V4 Flash 在高上下文推理方面优于 M2.7 和 Stepfun 3.7 等其他模型,但缺乏密集模型的世界知识。 AI

影响 展示了在专用硬件上运行大型模型的高上下文能力和性能调优。

排序理由 用户报告的特定模型和硬件配置的性能基准和配置详细信息。[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 Flash 在 DGX Spark 上实现 100 万上下文

本文如何被排名

Signal score
0 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
用户报告的特定模型和硬件配置的性能基准和配置详细信息。[lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
model release, infra
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
129 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

完整方法见我们的编辑标准。

报道来源 [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/Only_Situation_4713 ·

    Deepseek V4 在 DGX Spark 上闪电般地展示性能

    <!-- SC_OFF --><div class="md"><p>Hello Reddit</p> <p>I have been trying to get Deepseek V4 on the DGX Spark for the past week. Yesterday I was finally able to get it to work thanks to the hard work from the folks at <a href="https://github.com/local-inference-lab">local-inferenc…