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Ricursive releases Ripple-65B Preview, claiming $32M total cost for agentic coding gains

AIRicursive Intelligence released Ripple-65B Preview, a 65B dense LLM pretrained from scratch, and says it surpasses larger U.S. open-weight models in agentic coding. swyx, quoting the release, says the model cost $32M, one-tenth the cost of the previous open-weight SOTA on agentic coding. A footnote says the $32M covers full R&D, including pretraining ladder development, data mixing, evals, debugging, synthetic data generation, posttraining, and the final pretraining and posttraining runs.
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we developed and trained Ripple-65B Preview for only $32M, which is one-tenth the cost of the previous open-weight SOTA on agentic coding¹

this is like the avengers of open model SOTA

¹ "Note that $32M is our full R&D cost starting from scratch, including pretraining ladder development, data mixing, evals, debugging, synthetic data generation, posttraining recipe development, and the final hero pretraining and posttraining run."

Ricursive Intelligence@RicursiveAI
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://www.ricursive.com/ripple
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swyx · x.comPublished · added here

Original title: > we developed and trained Ripple-65B Preview for only $32M, which is one-tenth the cost of the previous open-weight SOTA on agentic coding¹

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