返回 2026-08-22 编辑版
发现与解读中文优先 · EN 原文AI 模型

Percy Liang 发布:Marin 535B-A23B 在 11 套 GB200 NVL72 上启动训练;Nathan Lambert 转发

为整个马林团队感到高兴。他们已经为此默默努力了很长时间。我很高兴能够在该模型的培训后与社区合作!

查看英文原文

So happy for the whole Marin team. They've been quietly working up to this for a long time. I'm excited to get to work with the community post-training this model!

So happy for the whole Marin team. They've been quietly working up to this for a long time. I'm excited to get to work with the community post-training this model!

开放模型从资产发布走向大规模训练、推理提速与软硬件协同

为什么值得看

训练计划、后训练优化与统一执行栈同时出现,说明开放模型竞争正在从单一权重扩展到完整工程系统。

最强反方

训练周期、速度和通用性均为项目方口径;Marin 仍在进行中,Lamb Labs 缺少独立复现,Modular 的日榜热度不等于生产采用。

原始出现与传播对照

1 条出现 · 本次 AIHOT 未精确命中

发现与解读

为整个马林团队感到高兴。他们已经为此默默努力了很长时间。我很高兴能够在该模型的培训后与社区合作!

为整个马林团队感到高兴。他们已经为此默默努力了很长时间。我很高兴能够在该模型的培训后与社区合作!

查看英文原文

So happy for the whole Marin team. They've been quietly working up to this for a long time. I'm excited to get to work with the community post-training this model!

So happy for the whole Marin team. They've been quietly working up to this for a long time. I'm excited to get to work with the community post-training this model!

直接发布标题Nathan Lambert@natolambert打开该层出处 ↗

So happy for the whole Marin team. They've been quietly working up to this for a long time. I'm excited to get to work with the community post-training this model!

被引用帖Percy Liang@percyliang打开该层出处 ↗

🚢 Marin 535B-A23B started training this week! As usual, the whole process is open. Voyage plan: pretraining (80%) + midtraining (20%) on 18.75T tokens on 11 x GB200 NVL72 for ~3 months (2.7e24 FLOPs). Post-training will follow. Before kicking off the run, we trained a 4-rung scaling ladder from 1.6B-A61M (48B tokens) to 27.7B-A1.2B (926B tokens) to debug issues, and to make a forecast of our hero run. This is by far our biggest run, so definitely expecting the unexpected.

来源
X @natolambert · x-natolambert
证据角色
x_open_model_network
时间状态
known
用户判决
未判
查看该来源原文raw/x-natolambert.json3d03d4d7daf4a6e97877032b053e44f53c363406cc2ae2ce95adf1314a25285d
Cluster IDevt_55b1a57ce93ee25f9cc239f0精确去重依据canonical_url事件状态未判