# Nemotron 3.5 Super VL

ElevenLabs and NVIDIA are expanding their partnership to bring NVIDIA's Nemotron open models into ElevenAgents, ElevenLabs' conversational agent platform, and to add 15 MW of Vera Rubin capacity on top of existing Blackwell Ultra systems. On the ElevenAgents benchmark for realistic customer-support tasks, Nemotron 3.5 Super VL reached leading end-to-end task-completion accuracy at 70% lower cost than other leading open models. The two companies are also applying voice agents to Poland's national e-Health central appointment system, with an on-premises deployment that keeps citizen data and audio within government infrastructure.

ElevenLabs and NVIDIA are expanding their partnership to bring NVIDIA's Nemotron open models into ElevenAgents, ElevenLabs' conversational agent platform, and to add 15 MW of Vera Rubin capacity on top of existing Blackwell Ultra systems. On the ElevenAgents benchmark for realistic customer-support tasks, Nemotron 3.5 Super VL reached leading end-to-end task-completion accuracy at 70% lower cost than other leading open models. The two companies are also applying voice agents to Poland's national e-Health central appointment system, with an on-premises deployment that keeps citizen data and audio within government infrastructure.

NVIDIA released Nemotron 3.5 Super VL, an open multimodal model that takes text, images, documents and video and returns text for always-on agents that read screens, documents and tools. SGLang supports deployment from day one, serving it with continuous batching, prefix caching and speculative decoding. The mixture-of-experts model has 120 billion total parameters and activates 12 billion per token, with built-in multi-token prediction; it reaches 243.9 tok/s on a single RTX 6000 PRO.

NVIDIA released Nemotron 3.5 Super VL, an open multimodal model that takes text, images, documents and video and returns text for always-on agents that read screens, documents and tools. SGLang supports deployment from day one, serving it with continuous batching, prefix caching and speculative decoding. The mixture-of-experts model has 120 billion total parameters and activates 12 billion per token, with built-in multi-token prediction; it reaches 243.9 tok/s on a single RTX 6000 PRO.

NVIDIA released Nemotron 3.5 Super VL, an open multimodal model now available for inference and training on Baseten, so agents can read documents, interpret application screens and analyze video directly. It builds on the Nemotron 3 Super architecture as a 120B-parameter Mixture-of-Experts model that activates 12B parameters per token, adding a vision encoder for image input. In NVIDIA's reported evaluations it scores an Elo of 1190 on GDPval versus 493 for Nemotron 3 Super, and also scores higher on SciCode and GPQA-diamond.

NVIDIA released Nemotron 3.5 Super VL, an open multimodal model now available for inference and training on Baseten, so agents can read documents, interpret application screens and analyze video directly. It builds on the Nemotron 3 Super architecture as a 120B-parameter Mixture-of-Experts model that activates 12B parameters per token, adding a vision encoder for image input. In NVIDIA's reported evaluations it scores an Elo of 1190 on GDPval versus 493 for Nemotron 3 Super, and also scores higher on SciCode and GPQA-diamond.

NVIDIA released Nemotron 3.5 Super VL, an open multimodal model for long-running agents that folds document, image, and video understanding together with reasoning, instruction following, and tool use in one model, reducing the need to deploy separate text and vision models. It uses a 120-billion-parameter mixture-of-experts design with 12 billion active parameters, combined with a hybrid Mamba-Transformer architecture, multi-token prediction, and NVFP4 quantization, and can be post-trained with NVIDIA NeMo on an organization's own data, tools, policies, and workflows. The stated comparison is up to 5x faster throughput on agentic tasks than other open models in its size category on a single GPU, and 4x faster task completion.

NVIDIA released Nemotron 3.5 Super VL, an open multimodal model for long-running agents that folds document, image, and video understanding together with reasoning, instruction following, and tool use in one model, reducing the need to deploy separate text and vision models. It uses a 120-billion-parameter mixture-of-experts design with 12 billion active parameters, combined with a hybrid Mamba-Transformer architecture, multi-token prediction, and NVFP4 quantization, and can be post-trained with NVIDIA NeMo on an organization's own data, tools, policies, and workflows. The stated comparison is up to 5x faster throughput on agentic tasks than other open models in its size category on a single GPU, and 4x faster task completion.

NVIDIA released Nemotron 3.5 Super VL, an open, customizable multimodal model for long enterprise agent workflows that need reasoning, tool use, and text, image, document, and video understanding. It uses a 120B-parameter mixture-of-experts architecture that activates 12B parameters per token, and NVIDIA reports up to 5x higher throughput on agentic tasks than other open models in its size class on a single GPU. Teams can post-train it with NeMo on their own data, tools, and workflows, and NVIDIA also released agentic tool-use, finance reasoning, and 40 vision-language datasets.

NVIDIA released Nemotron 3.5 Super VL, an open, customizable multimodal model for long enterprise agent workflows that need reasoning, tool use, and text, image, document, and video understanding. It uses a 120B-parameter mixture-of-experts architecture that activates 12B parameters per token, and NVIDIA reports up to 5x higher throughput on agentic tasks than other open models in its size class on a single GPU. Teams can post-train it with NeMo on their own data, tools, and workflows, and NVIDIA also released agentic tool-use, finance reasoning, and 40 vision-language datasets.

NVIDIA released three open Nemotron 3.5 models: the 120-billion-parameter Super VL for multimodal agentic tasks, which reaches leading accuracy on instruction following, tool use, multistep business workflows and visual understanding comparable with NVIDIA's largest reasoning model at roughly one-fifth the parameter count, plus the edge-oriented Bolt 74B-A9B 24GB and Bolt E4B 4GB. Super VL and Bolt 74B-A9B are available now, with Bolt E4B coming Oct. 23, covering deployments from enterprise servers down to local hardware.

NVIDIA released three open Nemotron 3.5 models: the 120-billion-parameter Super VL for multimodal agentic tasks, which reaches leading accuracy on instruction following, tool use, multistep business workflows and visual understanding comparable with NVIDIA's largest reasoning model at roughly one-fifth the parameter count, plus the edge-oriented Bolt 74B-A9B 24GB and Bolt E4B 4GB. Super VL and Bolt 74B-A9B are available now, with Bolt E4B coming Oct. 23, covering deployments from enterprise servers down to local hardware.