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What is Nemotron 3 Super?

The Nemotron-3 Super stands out as a groundbreaking addition to NVIDIA's Nemotron 3 series of open models, designed specifically to support advanced agentic AI systems capable of reasoning, planning, and executing complex multi-step workflows in challenging settings. It incorporates a distinctive hybrid Mamba-Transformer Mixture-of-Experts architecture that combines the streamlined capabilities of Mamba layers with the contextual richness offered by transformer attention mechanisms, enabling it to effectively handle long sequences and complicated reasoning tasks with notable precision and efficiency. By activating only a selected subset of its parameters for each token, this design greatly improves computational efficiency while ensuring strong reasoning skills, making it particularly suitable for scalable inference in demanding situations. With an impressive configuration of around 120 billion parameters, of which approximately 12 billion are engaged during inference, the Nemotron-3 Super significantly enhances its capacity for managing multi-step reasoning and facilitating collaborative interactions among agents in broad contexts. This combination of features not only empowers it to address a wide array of challenges in the AI landscape but also positions it as a key player in the evolution of intelligent systems. Overall, the model exemplifies the potential for future innovations in AI technology.

What is Holo4?

Holo4 is a family of agentic AI models developed by H Company for computer use and multi-step automation across desktop, web, mobile, terminal, MCP, and API environments. The series consists of Holo4 27B, a dense 27-billion-parameter model, and Holo4 35B-A3B, a 35-billion-parameter Mixture-of-Experts model with 3 billion active parameters. Rather than specializing exclusively in graphical interfaces or tool calling, Holo4 can click and type on screens, write and run its own code, and invoke MCP or API tools as different stages of a workflow require. The same model can therefore move between desktop applications, websites, Android applications, code sandboxes, and business APIs without switching to a separate model for each interface. H Company's Agentic Task Factory generated approximately 10,000 tasks across web applications, MCP servers, desktop software, and hybrid environments to support model development and evaluation. Holo4 underwent supervised fine-tuning on 127 billion tokens, with roughly three-quarters of that training data consisting of successful agentic trajectories covering desktop, web, MCP/API, and mobile tasks. Two reinforcement-learning experts were subsequently trained for desktop/web workflows and terminal/MCP/API workflows before being merged into the final generalist model. In H Company's evaluations, Holo4 27B scored 85.2% on OSWorld, 61.7% on OSWorld 2.0, 45.4% on AutomationBench, and 85.1% on AndroidWorld, although the company notes that reference-model results can use different harnesses and effort levels. Holo4 27B supports a 256K context window and is priced through the H Models API at $0.40 per million input tokens, $0.04 per million cached input tokens, and $3.00 per million output tokens. Holo4 35B-A3B also supports 256K context and is priced at $0.30 per million input tokens, $0.03 per million cached input tokens, and $2.00 per million output tokens.

Media

Media

Integrations Supported

Perplexity Computer
Perplexity Pro

Integrations Supported

Perplexity Computer
Perplexity Pro
Auggie CLI
Augment Code
Azure OpenAI Service
Bash
C++
ChatGPT Atlas
ChatGPT Enterprise
ChatGPT Health
Doraverse
GPT-5.4 mini
HTML
Microsoft Teams
Objective-C
OpenAI Dots
OpenCode
Rust
Scala
SpawnHQ

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

$0.40 per 1M tokens (input)
Input: $0.40 per 1 million tokens
Output: $3 per 1 million tokens

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

nvidia.com

Company Facts

Organization Name

H Company

Date Founded

2023

Company Location

France

Company Website

openai.com

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

Categories and Features

AI Models

Not specified

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Popular Alternatives

No Alternatives
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