English(EN) Frontier model performance on an open model, post-trained in under 24 hours. @trajectorylabs is showing what's possible when great open models meet the right tr

Trajectory Labs 在 24 小时内实现开放模型的前沿模型性能

作者 PulseAugur 编辑部 · [1 个来源] · 2026-06-11 19:22

Trajectory Labs 在一个开源模型上展示了前沿模型性能，在不到 24 小时的后训练时间内实现了这一壮举。这一成就凸显了强大的开放模型与高效训练基础设施相结合的潜力。Together Compute 与 Nvidia 合作，为这一快速开发提供了必要的计算能力。 AI

影响展示了开源模型的加速训练技术，可能降低了前沿水平人工智能开发的门槛。

排序理由该集群描述了模型训练效率方面的研究成果，而不是顶级实验室直接发布新的前沿模型。[lever_c_demoted from research: ic=1 ai=1.0]

在 X — Together (inference / OSS) 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: 0 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 该集群描述了模型训练效率方面的研究成果，而不是顶级实验室直接发布新的前沿模型。[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: 122 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]

X — Together (inference / OSS) TIER_1 English(EN) · togethercompute · 2026-06-11 19:22

前沿模型在不到24小时内完成开放模型上的训练。@trajectorylabs 展示了优秀开放模型与合适的训练相结合的可能性

Frontier model performance on an open model, post-trained in under 24 hours. @trajectorylabs is showing what's possible when great open models meet the right training infrastructure. Proud to power the compute behind this work alongside @nvidia .

本文如何被排名

报道来源 [1]

前沿模型在不到24小时内完成开放模型上的训练。@trajectorylabs 展示了优秀开放模型与合适的训练相结合的可能性

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