Jensen Huang on NVIDIA's Long-Term Commitment to Open Nemotron Models

Melvin Vivas · X video post · 2026-03-18 · 3:12 · 190 views · Open on X

Topics: Industry Trends & Job Market, LLM Fundamentals · Level: beginner

Summary

In this clip, Ahmad Osman, who moderates r/LocalLLaMA, asks Jensen Huang whether NVIDIA will keep releasing Nemotron models or whether recent releases only proved that NVFP4 training works. Huang says NVIDIA numbers its model families (GR00T, Cosmos, Nemotron, and CUDA as an example) because it plans to keep developing them. Its goal is open models near the frontier that people can rely on. Building its own models also lets NVIDIA co-design them with new silicon and software such as TensorRT-LLM, NVLink 72 and Dynamo.

Key points

• NVIDIA plans to keep releasing open foundation models: Nemotron 1, 2 and 3 are out, and a coalition has started for Nemotron 4.
• Nemotron 3 Super has just been released, and Nemotron 3 Ultra is coming next.
• Huang's reasoning: 'The reason why you number something is because you have an intention to continue.' CUDA went from 1 to 13.
• NVIDIA's goal is models near the frontier, not at the frontier. It wants open models the world can count on, with a yearly roadmap.
• Reason 2: building its own models lets NVIDIA tune the architecture for new silicon and system designs that others may not take advantage of.
• TensorRT-LLM let NVIDIA explore the limits of NVLink 72. Dynamo let it explore disaggregated inference, which led to licensing Groq's technology and bringing on its team.
• Model work and full-stack software and hardware work 'feed each other'.
• Some people worried Nemotron only existed to prove NVFP4 training works. Huang says the open-model investment is long term.

Resources mentioned

• NVIDIA AI (@NVIDIAAI) on X · person · x.com · free
  NVIDIA AI's official X account, which posts model releases and endpoint availability.
  Also in: Using Free OpenRouter Models (Nemotron 3.5) With Coworker (Melvin Vivas on X · notes), AI News Roundup: Claude Fable 5, Scientist AI, ZCode, NVIDIA RL (Melvin Vivas on X · notes), Running AI Locally: Rebuilding AIBackends as a Python Library with Open Models (Melvin Vivas on X · notes), Qwen3.5 Multimodal Model Now on NVIDIA AI Endpoints (Melvin Vivas on X · notes)
• NVIDIA Nemotron · tool · nvidia.com · free
  NVIDIA's family of open foundation LLMs, including Nemotron 3 Super and the upcoming Ultra.
  Also in: NVIDIA Agent Toolkit: open Nemotron models for domain-specific agents (Melvin Vivas on X · notes)
• r/LocalLLaMA · community · reddit.com · free
  Reddit community for running and discussing local and open LLMs.
• Ahmad Osman (@TheAhmadOsman) · person · x.com · free
  Local-LLM advocate and r/LocalLLaMA moderator who asked Jensen this question.
• NVIDIA Isaac GR00T · tool · developer.nvidia.com · free
  NVIDIA's open foundation model family for humanoid robots.
• NVIDIA Cosmos · tool · nvidia.com · free
  NVIDIA's open world foundation models for physical AI.
• CUDA · tool · developer.nvidia.com · free
  NVIDIA's GPU computing platform, needed for GPU-accelerated deep learning.
  Also in: AI DevBox v1.3.0: a GPU-ready Docker image with coding-agent CLIs (Melvin Vivas on X · notes), GPU-Ready AI Devbox Docker Image on Runpod (PyTorch 2.8 + CUDA 12.8) (Melvin Vivas on X · notes), Reusable GPU devbox: PyTorch/CUDA plus six coding agents (Melvin Vivas on X · notes)
• TensorRT-LLM · repo · github.com · free
  NVIDIA's open-source library for optimized LLM inference on NVIDIA GPUs.
• NVIDIA Dynamo · repo · github.com · free
  Open-source framework for distributed, disaggregated LLM inference serving.
• NVIDIA GB200 NVL72 (NVLink 72) · tool · nvidia.com · paid
  NVIDIA's rack-scale system with 72 GPUs connected by NVLink.
• NVFP4 · other · developer.nvidia.com · free
  NVIDIA's 4-bit floating-point format for low-precision training and inference.