Ricursive Intelligence designs chips with AI. For that platform they trained a language model from scratch, and this week they released the general-purpose variant, Ripple-65B Preview, on Hugging Face under Apache 2.0: 65B dense, 12T tokens, up to 1M context, built by a team that grew from 1 to 5 people during development. The company reports 80.52 on TerminalBench 2.1 for agentic coding and $32M for the entire R&D effort. Those aren’t independently verified figures here. Their model card notes that scores shifted between harnesses when they tried to reproduce other labs’ results, so the leaderboard comparisons need caution too. Anyone here pulled the weights and tried it on a real project yet? That’s the part I’d like to hear about beyond the launch numbers. Sources in the first comment. Sources: Ricursive Intelligence’s announcement ( https://www.ricursive.com/ripple ) and model card ( https://huggingface.co/ricursiveAI/Ripple-65B-Preview , Apache 2.0 LICENSE in the repo). submitted by /u/shoumikgoswami
Originally posted by u/shoumikgoswami on r/ArtificialInteligence