Stanford 教师团队 Ricursive Intelligence 发布 65B 开源模型 Ripple

A 65B dense model matching or beating a 501B sparse model on Terminal-Bench 2.1 would shift assumptions about how much parameter count matters for agentic coding. The Apache 2.0 licence and local runnability mean teams can self-host a competitive coding agent without API dependence. Benchmark figures here are company-reported, so independent verification should be the first stop before adopting it.

kimmonismus@kimmonismusSource

An open-weight 30B MoE with only ~4B active parameters makes speech-to-text with speaker diarisation and translation runnable on modest hardware, undercutting the usual cost of per-language ASR pipelines. Builders working on voice agents or meeting transcription can self-host one checkpoint instead of chaining multiple services. With 40-language coverage, it is a practical candidate for multilingual Southeast Asian speech workloads.

官方账号NVIDIA AI@NVIDIAAI11 sourcesSource