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Ricursive AI Releases Ripple-65B Preview: A 65B Dense Open-Weight Model Scoring 80.5 on Terminal-Bench 2.1

Ricursive Intelligence has released Ripple-65B Preview, a 65B dense open-weight model pretrained from scratch for agentic coding. It achieves 80.5 on Terminal-Bench 2.1, the top self-reported score among US open-weight models, and is available under Apache 2.0 with three checkpoints. The model uses a dense Transformer architecture, trained on 12T tokens with up to 1M context, and claims a full R&D cost of $32M. It trails larger MoE rivals on some benchmarks like SciCode and DeepSWE.

Why it matters: This is a concrete new model release with notable performance claims and open-weight availability, offering practical value for developers and researchers in agentic coding.

MarkTechPost1d agoScore 85

AI model releaseopen-weight modelsagentic coding

Models Editor selected

Axion 1.0: Open Agent Foundation Model with Simplified Training Recipe

Axion 1.0 is a fully open agent foundation model trained in just three stages: two supervised fine-tuning stages and reinforcement learning, avoiding complex techniques like DPO or on-policy distillation. It achieves competitive performance on agentic benchmarks and releases the complete training recipe, including data construction and code, for full reproducibility. The model demonstrates that strong agentic capabilities can be built with a simple, open approach.

Why it matters: Provides a concrete, recent AI development with a novel simplified training method and full open-source release, valuable for practitioners and researchers.

arxiv2d agoScore 82

agentic AImodel trainingopen-source AI