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English(EN) someone got deepseek v4 flash, a 284B model, running on a 64GB laptop. no GPU 6.4 to 9.7 tokens/sec by the author's own numbers (llama-modchip, apache 2.0, very

DeepSeek-V4 Flash 模型可在无 GPU 的 64GB 笔记本电脑上本地运行

一个拥有 2840 亿参数的模型 DeepSeek-V4 Flash 已成功在无需专用 GPU 的 64GB RAM 笔记本电脑上运行。作者报告的推理速度在每秒 6.4 到 9.7 个 token 之间。这一成就得益于一个名为 Llama-modchip 的工具,该工具在 Apache 2.0 许可下可用。 AI

影响 使得大型模型能够在消费级硬件上本地执行,从而可能提高 AI 应用的可访问性和隐私性。

排序理由 展示了一个大型语言模型在没有 GPU 的消费级硬件上运行。[lever_c_demoted from research: ic=1 ai=1.0]

在 Mastodon — mastodon.social 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 模型可在无 GPU 的 64GB 笔记本电脑上本地运行

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18 / 100
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Tool
展示了一个大型语言模型在没有 GPU 的消费级硬件上运行。[lever_c_demoted from research: ic=1 ai=1.0]
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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
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High
Clearly on-topic for AI-industry coverage.
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Breaking (< 6h)
Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

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报道来源 [1]

  1. Mastodon — mastodon.social TIER_1 English(EN) · mohith808 ·

    有人在 64GB 笔记本电脑上运行了 DeepSeek V4 Flash,一个 284B 模型。没有 GPU,作者自己的数据显示速度为 6.4 到 9.7 tokens/sec (llama-modchip, apache 2.0, very

    someone got deepseek v4 flash, a 284B model, running on a 64GB laptop. no GPU 6.4 to 9.7 tokens/sec by the author's own numbers (llama-modchip, apache 2.0, very new, few independent benchmarks yet) be honest: would you take ~8 tok/s free and local over a fast paid API? https:// g…