Ricursive releases Ripple-65B, a 65B coding model it says beat 975B rivals

Ricursive Intelligence released Ripple-65B Preview on November 4th, a 65-billion-parameter dense open-weight coding model that the Palo Alto company says scored 80.5 on TerminalBench 2.1 and cost $32 million to train. Co-founders Anna Goldie and Azalia Mirhoseini, creators of AlphaChip, built Ripple as a general-purpose variant of the proprietary model behind Ricursive's AI chip design platform; the company claims it beats 975-billion-parameter rivals on that agentic test. The model card both supports and limits the efficiency claim, so independent runs are needed to confirm whether developers get a locally deployable open-weight coding model that challenges much larger systems.

Ricursive releases Ripple-65B, a 65B coding model it says beat 975B rivals Goldie and Mirhoseini's chip-design lab released a 65B dense model it says scored 80.5 on TerminalBench 2.1 and cost $32M to train. By Ryan Merket https://runtimewire.com/author/ryan-merket · Published · Updated Primary source: x.com https://x.com/RicursiveAI/status/2118046765857546733 Why it matters Ripple is the first public model from a $4B chip-design startup built by AlphaChip's creators, and its own model card both supports and limits the efficiency claim. If independent runs confirm the TerminalBench result at 65B, developers get a locally deployable open-weight coding model that challenges much larger systems on one key agentic test. Ricursive Intelligence released Ripple-65B Preview on November 4th, a 65-billion-parameter dense language model that co-founders Anna Goldie and Azalia Mirhoseini built to power the Palo Alto company's AI chip design platform. They are now offering it as a general-purpose open-weight model. Ricursive announced the release in a thread on X https://x.com/RicursiveAI/status/2118046765857546733 and on its Ripple page https://www.ricursive.com/ripple , saying Ripple is a general-purpose variant of the proprietary model behind its chip design work.… When you purchase through links in our articles, we may earn a small commission https://runtimewire.com/affiliate-monetization-standards . This doesn’t affect our editorial independence.