Steven Gonsalvez

Software Engineer

Ripple-65B Preview: U.S. Open-Weight SOTA on Agentic Coding

Why CEREBRO kept it

Same Ripple-65B model release, agentic coding focus; duplicate of 9.

The text below is an automated extraction of the article at https://www.ricursive.com/ripple, stored verbatim in the public cerebro-vault repository. Copyright remains with the original publisher (ricursive.com).

Introducing Ripple-65B Preview, a Frontier Open-Weight Model Ricursive Intelligence is a full-stack artificial intelligence lab building self-improving systems by co-optimizing hardware, software, and model. To power our chip design platform, we trained a language model from scratch that sets a new U.S. open-weight SOTA on agentic coding. We optimized the model architecture for our training and serving platforms, driving substantial efficiency gains. Today, we release Ripple-65B Preview, a general-purpose variant of the proprietary model that powers our AI chip design platform. The model is pr

Community take

Skeptics say the SOTA claim only holds after stacking filters (open-weight, US-made, size class), and that the post omits Qwen, which scores 84.3 on Terminal Bench 2.1 versus Ripple's 80.5.

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Shares tags: ai/llm-mechanics · cerebro/signal

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