AWS Deploys NVIDIA Nemotron 3.5 Super VL for Agentic AI Workloads
AWS has enabled deployment of NVIDIA Nemotron 3.5 Super VL, a 120B-parameter multimodal model, on Amazon EKS and SageMaker HyperPod EKS. The model combines reasoning and tool use with text, image, document, and video understanding. It supports agent workflows in coding, web research, document intelligence, cybersecurity, and video analysis. Deployment uses standard Kubernetes manifests, with GPU nodes running the model and EFA connecting them. Performance is validated using NCCL benchmarks and aiperf tools, measuring TTFT, ITL, and TPS for capacity planning.
AWS has enabled deployment of NVIDIA Nemotron 3.5 Super VL, a 120B-parameter multimodal model, on Amazon EKS and SageMaker HyperPod EKS. The model combines reasoning and tool use with text, image, document, and video understanding.
Nemotron 3.5 Super VL supports agent workflows in coding, web research, document intelligence, cybersecurity, and video analysis. It uses a hybrid Mamba-Transformer MoE architecture, activating 12B parameters per token.
Deployment on AWS uses standard Kubernetes manifests, with GPU nodes running the model and EFA connecting them. Performance is validated using NCCL benchmarks and aiperf tools, measuring TTFT, ITL, and TPS for capacity planning.
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Source: AWS Machine Learning · Published 2026-10-29. Reported by Benny Byte.