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What is Nemotron 3.5 Super VL?

NVIDIA Nemotron 3.5 Super VL is an open multimodal artificial intelligence model designed to support specialized autonomous agents, enterprise automation, and complex reasoning tasks. Introduced in October 2026, the model combines language processing, visual understanding, software engineering capabilities, and external tool interactions within a unified architecture. It uses a 120-billion-parameter mixture-of-experts design with approximately 12 billion active parameters per token to optimize inference efficiency. The model was distilled from NVIDIA Nemotron 3 Ultra and incorporates additional training focused on coding, multimodal reasoning, and agentic task execution. Its vision-language capabilities support analysis of images, charts, tables, diagrams, multipage documents, and video content. Document intelligence workflows can extract structured information, interpret visual evidence, connect information across pages, and generate summaries or reports. Software engineering features enable the model to analyze repositories, identify programming errors, test code, and recommend modifications across development workflows. Its agentic capabilities support web research, external tool usage, multistep problem-solving, cybersecurity vulnerability analysis, and enterprise process automation. NVIDIA NeMo provides customization tools for supervised fine-tuning, low-rank adaptation, and reinforcement learning using proprietary datasets, organizational policies, and specialized workflows. The model incorporates LiLiCorr speculative decoding, multi-token prediction, context reuse, and NVFP4 quantization to improve inference performance on compatible hardware. Nemotron 3.5 Super VL is distributed with open weights and supports local, cloud, and data center deployment through NVIDIA infrastructure and tools such as NVIDIA NIM.

What is Command R?

Command's model generates outputs that include accurate citations, which significantly minimize the potential for misinformation while offering additional context from the original materials. It excels in various tasks such as crafting product descriptions, aiding in email writing, and suggesting sample press releases, among other functions. Users can interact with Command by posing multiple questions about a document to categorize it, extract specific details, or tackle general inquiries regarding the content. Addressing several questions related to a single document not only conserves valuable time but also applying this method to thousands of documents can result in considerable time savings for businesses. This collection of scalable models strikes an impressive balance between exceptional efficiency and solid accuracy, enabling organizations to evolve from initial experimentation to fully functional AI applications. By harnessing these advanced capabilities, companies can effectively boost their productivity and refine their operational workflows. In today's fast-paced business environment, such tools are indispensable for maintaining a competitive edge.

Media

Media

Integrations Supported

NVIDIA NIM
OpenRouter
vLLM

Integrations Supported

Azure Marketplace
BLACKBOX AI
Bind AI
Cohere
MindMac
Symflower
Wordware
thisorthis.ai

API Availability

Has API

API Availability

Pricing Information

$0
The model is available at no charge under the OpenMDW-1.1 license. Hosted inference through third-party providers may have separate charges.
Free Version

Pricing Information

Pricing not provided

Supported Platforms

SaaS
On-Prem
Linux

Supported Platforms

SaaS

Customer Service / Support

Not specified

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Not specified

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

nvidia.com

Company Facts

Organization Name

Cohere AI

Date Founded

2019

Company Location

Canada

Company Website

cohere.com/command

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

AI Reasoning Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Multimodal Models

Not specified

Open-Weight AI Models

Not specified

Categories and Features

AI Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

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