Nathan Lambert 评 Ripple-65B：小团队也能做出扎实模型
Love this scrappy project. Hoping more US labs follow suit, showing they can also make solid models with small focused teams. This also intellectually follows o
Nathan Lambert 评论 Ricursive Intelligence 发布的 Ripple-65B Preview，称这是一个有冲劲的项目，希望更多美国实验室效仿，用小而专注的团队做出扎实模型。他指出该模型在思路上延续了 olmo 系列，看到自己参与的项目被放大很有意义。被引推文称 Ripple-65B 是从零预训练的 65B 稠密大语言模型，在美国开放权重模型的智能体编码任务上超过 Muse Spark Open-816B、Beam-501B、Inkling-975B 和 Nemotron 3 Ultra-550B 等更大模型。
查看原帖今天我们发布 Ripple-65B Preview，这是我们从头预训练的 65B 稠密大语言模型。 Ripple 在美国开放权重模型的智能体编码任务上树立了新的最先进水平，显著超越了包括 Muse Spark Open-816B、Beam-501B、Inkling-975B 和 Nemotron 3 Ultra-550B 在内的更大模型。 了解更多：https://t.co/Pe04ZKhkE9
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Today we release Ripple-65B Preview, our 65B dense LLM we pretrained from scratch. Ripple sets a new state-of-the-art for U.S. open-weight models in agentic coding tasks, surpassing significantly larger models including Muse Spark Open-816B, Beam-501B, Inkling-975B, and Nemotron 3 Ultra-550B. Learn more: https://t.co/Pe04ZKhkE9
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Love this scrappy project. Hoping more US labs follow suit, showing they can also make solid models with small focused teams. This also intellectually follows on the olmo lineage, so super cool to see what our baby looks like scaled up.