😺 🎙️ Watch: NVIDIA's 120B Model Runs Like a 12B. Here's How.

2026-03-19 · Source: The Neuron · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Robotics & Autonomous Systems, Software Development & Engineering · Depth: Intermediate, long

Summary

NVIDIA unveiled Nemotron-3 Super, a 120 billion parameter AI model that performs with the efficiency of a 12 billion parameter model, running at three times the speed of Meta's Llama 70B on a standard GPU like an RTX 4000. This advancement, attributed to "mixture of experts" architecture, allows for local execution without a data center. Nemotron-3 is the core intelligence for NemoClaw, NVIDIA's new open-source runtime for secure, always-on OpenClaw AI agents that can perform actions like sending emails or managing files. The announcement was made at NVIDIA GTC 2026, where CEO Jensen Huang emphasized the necessity of an OpenClaw strategy for companies. NVIDIA also highlighted the rapid 35x growth in open-source AI token generation over the past year.

Key takeaway

For CTOs and Directors of AI/ML evaluating AI deployment strategies, NVIDIA's Nemotron-3 Super and NemoClaw signal a shift towards powerful, locally deployable open-source AI agents. Your teams should investigate integrating Nemotron-3 for applications requiring high-parameter models with efficient local inference, potentially reducing reliance on cloud infrastructure and enhancing data privacy through on-premise agentic AI.

Key insights

NVIDIA's Nemotron-3 Super enables large AI models to run efficiently on consumer GPUs via a mixture of experts.

Principles

• Open-source AI is infrastructure.
• Harness engineering defines AI product value.
• Proprietary and open models coexist.

Method

NVIDIA's Nemotron-3 Super utilizes a "mixture of experts" architecture, allowing a 120B parameter model to activate only 12B parameters at a time, significantly boosting speed and reducing hardware requirements for local execution.

In practice

• Run Nemotron-3 Super on an RTX 4000 GPU.
• Deploy OpenClaw AI agents on local hardware.
• Explore Nemotron-3 Nano for low-memory systems.

Topics

• NVIDIA GTC
• Nemotron 3
• AI Agents
• Mixture-of-Experts
• Open-Source AI

Code references

• NVIDIA/NemoClaw

Best for: CTO, Director of AI/ML, MLOps Engineer, AI Engineer, Machine Learning Engineer, AI Architect

Related on AIssential

• AI 101: Nemotron 3 and the Surprising Coalition Building New AI in the Open — NVIDIA's Nemotron initiative fosters open AI development through collaborative models and a comprehensive open-source stack.
• GTC Spotlights NVIDIA RTX PCs and DGX Sparks Running Latest Open Models and AI Agents Locally — Generative AI agents are shifting from cloud to local devices, driven by new open models and optimized software stacks.
• Even the chip makers are making LLMs — NVIDIA's co-design of hardware and fully open-source LLMs drives mutual optimization and fosters broad AI development.
• NVIDIA’s New AI Just Changed Everything — NVIDIA's Nemotron 3 Super offers a powerful, open-source AI assistant with significant speed improvements via novel architectural and mathematical techniques.
• I Gave an AI Agent Root Access to a Sandboxed Linux Box. It Didn’t End How I Expected. — NVIDIA has released NemoClaw, an open-source stack enabling always-on, self-evolving AI agents to run within a hardened sandbox on local machines with a single command.
• Together AI at NVIDIA GTC 2026: Explore our latest innovations across research and products — Together AI and NVIDIA are advancing open, agentic, and production-ready AI systems through new model integrations and inference optimizations.

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Editorial summary, takeaway, and curation by AIssential. Original article published by The Neuron.