Nemotron - Nvidia Agentic AI

--https://share.google/aimode/atYpjUfqCK4r96o9R

NVIDIA Nemotron is an open-weights family of high-efficiency, multimodal AI models developed by NVIDIA and optimized for building complex, high-throughput agentic AI systems. [1, 2]

Key Architecture & Sizes

Hybrid Mixture-of-Experts (MoE): Combines Mamba and Transformer architectures to maximize reasoning throughput while minimizing inference costs and latency. [1, 2]
Nemotron 3 Nano: Compact, edge-efficient model optimized for low-latency perception and sub-agent workflows (including variants like Nano Omni with native audio, video, and image support). [1, 2]
Nemotron 3 Super: Mid-sized model tailored for high-throughput reasoning and function/tool calling in multi-agent production setups. [1]
Nemotron 3 Ultra: Massive frontier model (around 550B parameters) built for deep, mission-critical autonomous reasoning and complex enterprise workflows. [1, 2]

Core Features

Massive Context: Supports up to 1-million-token context windows in major configurations, allowing agents to retain extensive codebases, videos, or lengthy documents. [1, 2]
Full Transparency: Provides open weights, open training recipes, and transparently documented training datasets via Hugging Face and GitHub. [1, 2]
Flexible Deployment: Easily deployable across edge devices, single GPUs, and data centers using frameworks like vLLM, SGLang, Ollama, llama.cpp, or NVIDIA NIM microservices. [1, 2]

If you'd like, let me know:

• Are you looking to deploy a specific model size (Nano, Super, Ultra)?
• Do you need help with a particular framework (such as Ollama or vLLM)?