Ricursive's self-trained 65B model: Developed by a 5-person R&D team, its programming capabilities are approaching the top tier of US open-source models.
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Beating AI News Flash: Ricursive Intelligence, an AI company founded by former Google DeepMind researchers, has released the open-source model Ripple-65B Preview. The two founders previously led the AlphaChip project, which uses AI to automatically optimize Google TPU chip layouts. Ripple is a 65-billion-parameter dense model trained from scratch, utilizing 12 trillion tokens of training data and supporting a maximum context window of 1 million tokens. In the official Terminal-Bench 2.1 programming test, it scored 80.5%, slightly outperforming the 501-billion-parameter Reflection Beam (80.1%) and surpassing the 975-billion-parameter Inkling (63.8%). Ricursive stated that the entire model development cost only $32 million, with the team expanding from 1 to 5 members during development. The company improved training efficiency by refining model architecture, training data, and reinforcement learning methods. In control experiments with 4-billion-parameter models, the computing power required to achieve comparable code capability was reduced by approximately 16 times. Ripple’s model weights are now open-sourced under the Apache 2.0 license; after quantization, it is expected to occupy around 36–40GB, and can theoretically run locally on Mac devices with 64GB or more of memory.
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