Ricursive Intelligence Releases Ripple 65B Preview and Says It Leads US Open Weight Models in Agentic Coding
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:
Context
A US lab claiming the best American open weight coding model from a 65B model trained from scratch adds pressure on the open model race with China.
Ricursive Intelligence (@RicursiveAI) trained Ripple from scratch. A dense model uses all its parameters for every token, unlike mixture of experts models. Agentic coding tests measure how well a model completes multi step programming tasks with tools.
Deep dive
Ricursive Intelligence (@RicursiveAI) posted on Nov 4 that it is releasing Ripple 65B Preview, a 65 billion parameter dense language model that it pretrained from scratch.
According to Ricursive, Ripple sets a new state of the art for US open weight models in agentic coding tasks. The company says it beats much larger models, naming Muse Spark Open, Beam, Inkling and Nemotron 3 Ultra, each listed in the post with hundreds of billions of parameters.
These results come from the company and are not independently confirmed in the post. The post does not list the benchmarks used or the scores, which sit behind the linked page. The word Preview suggests a fuller release is planned.
The claim is narrow on purpose: best among US open weight models, not best overall. That matters because the strongest open weight models have mostly come from Chinese labs, including Moonshot's Kimi K3.1 Pro, whose weights were released today. A smaller US model winning on coding agents would give American companies a strong option they can run themselves.
The post passed 340,000 views.
What to expect next
Watch for independent agentic coding results, the license, and a full release after the preview. Developers will compare Ripple with Kimi K3.1 Pro and other Chinese open models. If the claims hold, inference providers and US companies that avoid Chinese models may adopt it quickly, and Ricursive may raise money or announce larger models.
A full model card with training data, compute and evaluation details would also help outsiders judge the preview fairly.