Ricursive Intelligence

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@RicursiveAI

ricursive.com

Palo Alto, CA Joined October 2025

0 Following 9.4K Followers 132 Posts

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Ricursive Intelligence @RicursiveAI 3d

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: ricursive.com/ripple

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Ricursive Intelligence @RicursiveAI 2d

Now live on Fireworks and Together as well! All inference endpoints available below:

Fireworks: fireworks.ai/models/firewor…
Together: together.ai/models/ripple-…
GMI Cloud: console.gmicloud.ai/model/llm/ripp…
OpenRouter: openrouter.ai/ricursiveai/ri…

fireworks.ai Ripple-65B Preview API & Playground | Fireworks AI Use of the Ripple-65B Preview model is subject to the Apache 2.0 license on its Hugging Face page.

Ricursive Intelligence @RicursiveAI 3d

Thank you for your kind words!

Yes, our $32M R&D cost fully encompasses our pretraining ladder development, data mixing, evals, debugging, synthetic data generation, posttraining recipe development, and the final hero pre, mid, and posttraining run!

swyx 🔜 aie.codes Verified account @swyx 3d

> we developed and trained Ripple-65B Preview for only $32M, which is one-tenth the cost of the previous open-weight SOTA on agentic coding¹

this is like the avengers of open model SOTA

¹ "Note that $32M is our full R&D cost starting from scratch, including pretraining ladder development, data mixing, evals, debugging, synthetic data generation, posttraining recipe development, and the final hero pretraining and posttraining run."

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Ricursive Intelligence @RicursiveAI 3d

Thanks for a great partnership @nvidia!

NVIDIA RTX Spark Verified account @NVIDIARTXSpark 3d

Congrats to @RicursiveAI on Ripple-65B Preview, their first open model 🎉

It was trained on NVIDIA B300 GPUs & sharpened with open NVIDIA Nemotron post-training datasets.

Download the NVFP4 checkpoint from Hugging Face and run locally on DGX Spark 👉 huggingface.co/ricursiveAI/Ri…
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Ricursive Intelligence @RicursiveAI 3d

Thank you for your genuine support @kimmonismus. We're just getting started!

Chubby♨️ Verified account @kimmonismus 3d

Ok, *this is impressive*: Ricursive Intelligence just released Ripple-65B Preview, an open-weight AI model that it says outperforms much larger US models on a key agentic coding benchmark. And even runs locally on my DGX Spark.

Ripple scored 80.5% on Terminal-Bench 2.1, narrowly ahead of Reflection’s Beam-501B at 80.1%, according to the companies’ reported results!

The size comparison comes with a detail: Ripple uses all 65B parameters for each task, while Beam activates 23B of its 501B parameters.

Ricursive says Ripple was trained on 12 trillion tokens with a $32 million compute budget - from scratch. The model supports up to 1 million tokens of context and is available under Apache 2.0.

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