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NVIDIA Nemotron 3.5 Super VL model accelerates agentic AI on AWS

NVIDIA has released its Nemotron 3.5 Super VL, a 120-billion parameter open multimodal model, designed to accelerate agentic AI applications. This model integrates reasoning and tool use with text, image, document, and video understanding, enabling it to handle both text and visual tasks. It features a hybrid Mamba-Transformer MoE architecture and can be deployed on AWS services like Amazon EKS and SageMaker HyperPod EKS. AI

IMPACT Enables more sophisticated agentic AI applications by combining reasoning with multimodal understanding, potentially accelerating development in areas like coding and cybersecurity.

RANK_REASON New model release from a frontier lab (NVIDIA). [lever_c_demoted from frontier_release: ic=2 ai=1.0]

Read on Mastodon — mastodon.social →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

NVIDIA Nemotron 3.5 Super VL model accelerates agentic AI on AWS

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54 / 100
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Significant
New model release from a frontier lab (NVIDIA). [lever_c_demoted from frontier_release: ic=2 ai=1.0]
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2 independent sources
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model release, infra
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COVERAGE [2]

  1. AWS Machine Learning Blog TIER_1 English(EN) · Alex Iankoulski ·

    Accelerate agentic AI with NVIDIA Nemotron models on Amazon EKS and SageMaker HyperPod EKS

    NVIDIA Nemotron 3.5 Super VL is a 120B-parameter mixture-of-experts model that pairs reasoning and tool use with multimodal understanding. This post explores its architecture and use cases, then shows how to deploy it on Amazon EKS, EKS Auto Mode, and Amazon SageMaker HyperPod EK…

  2. Mastodon — mastodon.social TIER_1 English(EN) · [email protected] ·

    🤖 Accelerate agentic AI with NVIDIA Nemotron models on Amazon EKS and SageMaker HyperPod EKS NVIDIA Nemotron 3.5 Super VL is a 120B-parameter mixture-of-experts

    🤖 Accelerate agentic AI with NVIDIA Nemotron models on Amazon EKS and SageMaker HyperPod EKS NVIDIA Nemotron 3.5 Super VL is a 120B-parameter mixture-of-experts model that pairs reasoning and tool use with multimodal understanding. This post explores its architecture and use case…