English(EN) DeepSeek MLA: 70 GB of KV Cache at 1M Tokens No DeepSeek-V4 config is public yet. The V3 one is, and its KV-cache math tells you what a million-token window act

DeepSeek V4需要70GB KV缓存以支持100万token上下文

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-07 05:03

DeepSeek最新模型DeepSeek V4需要高达70GB的KV缓存来处理100万token的上下文窗口。虽然V4的具体配置尚未公开，但V3模型的细节揭示了处理如此大上下文长度所带来的显著GPU内存需求。 AI

影响凸显了前沿模型中大上下文窗口所需的显著基础设施成本和内存要求。

排序理由前沿实验室模型发布，系统卡[lever_c 从 frontier_release 降级：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 →

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Signal score: 3 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Significant; 前沿实验室模型发布，系统卡[lever_c 从 frontier_release 降级：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: Same-day; Cluster formed today. Ranking reflects the current source set at time of score.

完整方法见我们的编辑标准。

报道来源 [1]

Mastodon — mastodon.social TIER_1 English(EN) · pickuma · 2026-09-07 05:03

DeepSeek MLA：70 GB KV 缓存支持 100 万 Token，DeepSeek-V4 配置尚未公开。V3 配置已公开，其 KV 缓存计算揭示了百万 Token 窗口的运作方式

DeepSeek MLA: 70 GB of KV Cache at 1M Tokens No DeepSeek-V4 config is public yet. The V3 one is, and its KV-cache math tells you what a million-token window actually costs in GPU memory. https:// pickuma.com/for-dev/deepseek-m la-kv-cache-million-token-context/?utm_source=mastodo…

链接 pickuma.com/…/deepseek-mla-kv-cache-milli…

本文如何被排名

报道来源 [1]

DeepSeek MLA：70 GB KV 缓存支持 100 万 Token，DeepSeek-V4 配置尚未公开。V3 配置已公开，其 KV 缓存计算揭示了百万 Token 窗口的运作方式

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