❯ Nvidia releases the open Nemotron 3.5 Super VL, with up to 5x the agentic throughput of similar-sized models on a single GPU

One model for text and imagesNvidia released Nemotron 3.5 Super VL on October 15, an open, customizable multimodal model. Its mixture-of-experts architecture has 120 billion parameters and activates 12 billion per token, combining reasoning, tool use and understanding of text, images, documents and video in one model, so companies need not deploy separate text and vision models.

5x throughput on one GPUNvidia says that on a single GPU it delivers up to 5x the agentic throughput of other open models in its size class. Companies including Scale AI, Ramp and AI21 have post-trained it on their own data, and Nvidia cites results such as 40x lower inference cost, 10x lower latency and 40% higher accuracy; these figures are Nvidia’s own.

The chip seller makes models tooDevelopers can keep training it with Nvidia’s NeMo toolkit and open datasets on Hugging Face, and the model is optimized for inference on Nvidia platforms such as DGX Spark. The same day, Meta released the larger Muse Spark Open. Companies have more open models to choose from, and Nvidia’s approach ties its model to its own hardware and software so customers do their customization on its platform.

▮ SIGNALBy making its own open models, Nvidia is really selling a path to customization that runs fastest on its chips, turning the model into a sales tool for its compute platform.