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English(EN) dgx sparks and new models my tests and results

新的大语言模型基准测试显示 Qwen3.8 Flash Next 在 DGX Sparks 上领先

一位 r/LocalLLaMA 上的用户分享了包括 DeepSeek V4 FlashQwen3.8 Flash NextQwen3.8-27BQwen3.6-35B-A3B 在内的几款新大语言模型的性能基准测试。测试在 NVIDIA DGX Spark 硬件上进行,重点关注运行时间、服务上下文长度和每秒交付的 token 数等指标。Qwen3.8 Flash Next 模型,尤其是在“中等”设置下,取得了最高的 22/24 分,而其“低”设置提供了更好的日常平衡。DeepSeek V4 Flash 展示了强大的输出 token 生成能力,但运行时间显著延长。 AI

影响 为在 DGX 硬件上运行本地大语言模型的用户提供了实用的性能数据,突出了速度、上下文长度和输出质量之间的权衡。

排序理由 用户在特定硬件上对多个大语言模型进行的基准测试。[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 →

新的大语言模型基准测试显示 Qwen3.8 Flash Next 在 DGX Sparks 上领先

本文如何被排名

Signal score
9 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
用户在特定硬件上对多个大语言模型进行的基准测试。[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
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
Breaking (< 6h)
Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

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/jtsaint333 ·

    dgx火花与新模型我的测试与结果

    <!-- SC_OFF --><div class="md"><p>We have four Sparks, arranged as two ConnectX-7 pairs. Over the last week we tried DeepSeek V4 Flash, Qwen3.8 Flash Next, Qwen3.8-27B and Qwen3.6-35B-A3B. The following tables are our preserved local results—not estimates copied from model cards.…