English(EN) RT @SkylerMiao7: M3 brings sparse attention + 1M context + multimodality, and Together did the hard serving work to make it fast.

MiniMax M3 模型支持 1M 上下文和多模态功能

作者 PulseAugur 编辑部 · [3 个来源] · 2026-06-03 04:52

MiniMax AI 发布了其 M3 模型，该模型具有增强的速度和一百万个 token 的上下文窗口。该模型还集成了稀疏注意力机制和多模态能力。Together AI 在优化 M3 模型以实现快速服务方面发挥了关键作用。 AI

影响在上下文窗口长度方面设定了新的 SOTA；向竞争对手施压，要求其匹配多模态和速度的改进。

排序理由 Frontier-lab 模型发布，附带系统卡。[lever_c_demoted from frontier_release: ic=2 ai=1.0]

AI 生成摘要 · Google Gemini · 来自 3 个来源。我们如何撰写摘要 →

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: Significant; Frontier-lab 模型发布，附带系统卡。[lever_c_demoted from frontier_release: ic=2 ai=1.0]
Source corroboration: 3 independent sources; Multiple independent publishers reporting the same story raises confidence that it's real and newsworthy.
Topics: model release, product; 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: 128 days old; Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.
Coverage growth since scoring: +1 source(s) since last score; New sources have picked up this story since our last re-score. Score will update on the next scoring pass.

完整方法见我们的编辑标准。

X — Together (inference / OSS) TIER_1 English(EN) · togethercompute · 2026-06-03 05:44

RT @SkylerMiao7: M3 带来了稀疏注意力 + 1M 上下文 + 多模态，Together 则完成了使其快速运行的艰巨工作。

RT @SkylerMiao7: M3 brings sparse attention + 1M context + multimodality, and Together did the hard serving work to make it fast. Great co…
X — MiniMax AI TIER_1 English(EN) · MiniMax_AI · 2026-06-03 04:56

RT @VictorSuOrtiz: 我们听取了意见，并付诸行动。MiniMax M3 比以往任何时候都更快。

RT @VictorSuOrtiz: We heard, and we executed. MiniMax M3 faster than ever.
X — MiniMax AI TIER_1 English(EN) · MiniMax_AI · 2026-06-03 04:52

RT @SkylerMiao7: M3 带来了稀疏注意力 + 100 万上下文 + 多模态，Together 公司则完成了使其快速运行的艰巨工作。

RT @SkylerMiao7: M3 brings sparse attention + 1M context + multimodality, and Together did the hard serving work to make it fast. Great co…