Nemotron 3.5 Super VL登陆AWS
AWS宣布NVIDIA Nemotron 3.5 Super VL现已与平台上的其他Nemotron模型一同提供。该模型采用1200亿参数的多模态MoE架构，每token激活120亿参数，支持文本、图像、文档和视频输入，可通过Amazon EKS、EKS Auto Mode及SageMaker HyperPod EKS部署。
AWS提供了该开放模型的可执行部署方案，可将推理、工具使用与视觉理解结合，用于在托管Kubernetes基础设施上构建多模态智能体工作负载。
NVIDIA Nemotron 3.5 Super VL joins the NVIDIA Nemotron 3 Nano, Nano Omni, Super, Ultra, and Nemotron 3.5 Lightning models already available on AWS. It’s a 120B-parameter mixture-of-experts (MoE) model that activates 12B parameters per token. It combines reasoning and tool use with text, image, document, and video understanding, so one model serves both text and visual tasks. This post explores its architecture and use cases, then shows how to deploy it on Amazon Elastic Kubernetes Service (Amazon EKS), Amazon EKS Auto Mode, and Amazon SageMaker HyperPod EKS.
About Nemotron 3.5 Super VL
NVIDIA Nemotron 3.5 Super VL is an open multimodal model distilled from Nemotron 3 Ultra. NVIDIA publishes the weights, training datasets, and post-training recipes, so you can customize the model for domain-specific workloads and run it on infrastructure you control. Model details:
- 120B total parameters, 12B active per token.
- Hybrid Mamba-2, MoE, and attention layers with a RADIO vision encoder.
- Context length up to 1M tokens.
- Input: text, image, document, and video.
- Output: text.
- BF16 and NVFP4 checkpoints.
#NVIDIA#NVIDIA Nemotron 3.5 Super VL#AWS#Amazon EKS#EKS Auto Mode#Amazon SageMaker HyperPod EKS