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About

NVIDIA Nemotron 3.5 Super VL is an open, customizable multimodal AI model designed for complex reasoning, autonomous agents, and enterprise workflows. The model uses a 120-billion-parameter mixture-of-experts architecture that activates approximately 12 billion parameters per token to balance computational efficiency with model capabilities. It combines text, image, document, and video understanding with instruction following, coding, and external tool use. Its multimodal capabilities support document analysis, chart interpretation, optical character recognition, video understanding, and automated information extraction. Developers can customize the model through supervised fine-tuning, low-rank adaptation, and reinforcement learning using NVIDIA NeMo. Nemotron 3.5 Super VL supports deployment in local, cloud, and data center environments for applications such as software engineering, financial document processing, cybersecurity analysis, and enterprise automation.

About

North Mini Code is Cohere’s first agentic coding model for developers and the inaugural member of its next generation of powerful models. Small, efficient, and open-source, it is built for the sovereign developer ecosystem and designed to deliver strong software development performance without requiring extensive hardware. North Mini Code is a mixture-of-experts model with 30B total parameters and 3B active parameters, giving developers access to agentic coding capabilities in a compact and efficient form. The model is optimized for code generation, agentic software engineering, and terminal tasks, with a 256K total context length and up to 64K maximum generation. It is built for real-world developer workflows, including understanding and orchestrating sub-agents, mapping system architecture, running code reviews, and supporting coding agents that need to reason through complex software tasks.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Supported
Cloud Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Not Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

AI developers, machine learning engineers, enterprise AI teams, software engineers, cybersecurity researchers, data scientists, financial technology companies, and organizations building customizable multimodal agents for document intelligence, coding, video analysis, and automated business workflows

Audience

Developers seeking to run efficient open-source AI models for code generation, agentic software engineering, terminal tasks, and code reviews

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Not Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Supported

API

Offers API Not Supported

Screenshots and Videos

Screenshots and Videos

Pricing

$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 Supported
Free Trial Not Supported

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Pros & Cons from Real Users

Pros

  • The agent performance is probably the biggest win. It is strong for coding, web research, document analysis, cybersecurity, and other multi-step tasks where the model has to understand what it is looking at and then actually do something with that information. I also really like the efficiency. NVIDIA says the 120B model only activates 12B parameters per token and can hit more than 600 output tokens per second in some agentic evaluations, which makes it much more practical for high-volume workflows than the headline model size suggests. The openness is another advantage. NVIDIA is releasing model checkpoints, datasets, training recipes, and customization tools through NeMo, so teams can adapt it to their own documents, policies, tools, and specialized workflows instead of depending entirely on a closed API.

Cons

  • This is not the model I would pick if I just wanted the easiest plug-and-play chatbot experience.

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Supported
Live Online Supported
In Person Not Supported

Company Information

NVIDIA
Founded: 1993
United States
nvidia.com

Company Information

Cohere
Founded: 2019
Canada
cohere.com/blog/north-mini-code

Alternatives

Alternatives

GLM-5.2

GLM-5.2

Z.ai
SWE-2

SWE-2

Cognition
Kimi K2

Kimi K2

Moonshot AI

Categories

AI Coding Models Supported
AI Models Supported
Foundation Models Supported
Multimodal Models Supported

Categories

AI Coding Models Supported
AI Models Supported

Integrations

NVIDIA NIM Supported
OpenCode Not Supported
OpenRouter Supported
vLLM Supported

Integrations

NVIDIA NIM Not Supported
OpenCode Supported
OpenRouter Not Supported
vLLM Not Supported
Claim Nemotron 3.5 Super VL and update features and information
Claim Nemotron 3.5 Super VL and update features and information
Claim North Mini Code and update features and information
Claim North Mini Code and update features and information