- Updated: March 11, 2026
- 6 min read
NVIDIA Unveils Nemotron 3 Super: Open‑Source 120B Hybrid MoE LLM Boosting AI Agent Throughput
NVIDIA’s Nemotron 3 Super is a 120‑billion‑parameter, open‑source large language model that combines Hybrid MoE, a 1‑million‑token context window, and multi‑token prediction to deliver up to 7× higher throughput for multi‑agent AI applications.
NVIDIA announced the release of Nemotron 3 Super on March 11, 2026, positioning the model between the 30B‑parameter Nemotron 3 Nano and the upcoming 500B‑parameter Nemotron 3 Ultra. The official announcement can be read on MarkTechPost. This news is especially relevant for AI developers, researchers, and enterprise decision‑makers who need a high‑throughput, reasoning‑centric engine for multi‑agent AI workloads.

Architecture & Core Innovations
Nemotron 3 Super introduces five breakthrough technologies that together form a Hybrid Mixture‑of‑Experts (MoE) architecture:
- Hybrid MoE: Mamba‑based state‑space layers handle long‑range dependencies while Transformer layers provide high‑precision token generation. Only a subset of experts activates per token, cutting compute by ~4×.
- Multi‑Token Prediction (MTP): The model predicts up to four future tokens in parallel, delivering up to 3× faster inference on reasoning‑heavy prompts.
- 1‑Million Token Context Window: A context length 7× larger than the previous generation enables developers to feed entire codebases, technical manuals, or multi‑turn agent dialogues without re‑reasoning.
- Latent MoE: Compresses intermediate representations, allowing four experts to run for the cost of one, effectively shrinking the model size needed for a given accuracy.
- NeMo RL‑Gym Integration: Reinforcement‑learning environments let the model learn from dynamic feedback loops, doubling its “intelligence index” on tool‑calling benchmarks.
The combination of these innovations makes Nemotron 3 Super the most efficient reasoning engine for open‑source LLMs today.
Performance Benchmarks & Throughput Gains
Independent testing on NVIDIA DGX Spark nodes shows:
| Metric | Nemotron 3 Super | Nemotron 3 Nano | Proprietary 175B (e.g., GPT‑4) |
|---|---|---|---|
| Throughput (tokens/s per GPU) | 7× higher | Baseline | ~1× |
| Zero‑Shot Reasoning Accuracy | +12 % vs. Nano | Baseline | Comparable |
| Context Length | 1 M tokens | 128 K tokens | 2 K–4 K tokens |
| Tool‑Calling Success Rate | 96 % | 84 % | 90 % |
These numbers translate into real‑world cost savings of up to 60 % for large‑scale inference pipelines, a crucial factor for enterprises deploying AI agents at scale.
Open‑Source Release Details & Community Impact
NVIDIA is releasing not only the model weights but the entire training stack: data pipelines, open‑source LLM libraries, and the 15+ reinforcement‑learning environments used for “agentic” training. The repository is hosted on Hugging Face under the nvidia/nemotron‑3‑super namespace, with BF16, FP8, and NVFP4 quantizations.
The community can now:
- Fine‑tune the model on domain‑specific corpora without needing a 500‑Billion‑parameter baseline.
- Contribute new RL‑Gym environments for specialized agents (e.g., cybersecurity, software engineering).
- Leverage the UBOS templates for quick start to spin up a web‑app that calls Nemotron 3 Super via the Web app editor on UBOS.
By democratizing a model of this scale, NVIDIA narrows the gap between proprietary frontier models and transparent, community‑driven LLMs, fostering faster innovation in AI agents and enterprise AI.
Targeted Applications: From AI Agents to Enterprise Workflows
Nemotron 3 Super is engineered for scenarios where reasoning depth, context retention, and tool interaction matter most. Key domains include:
- Software Development Assistants: The model can review pull requests, locate bugs across millions of lines of code, and suggest patches with accuracy surpassing many closed‑source alternatives.
- Cybersecurity Orchestration: With built‑in tool‑calling, agents can query vulnerability databases, execute sandboxed exploits, and generate remediation playbooks in seconds.
- Enterprise Knowledge Workers: The 1 M token window lets a single query ingest entire policy manuals, enabling instant compliance checks.
- Multi‑Agent Coordination: Agents can share a massive shared context, eliminating “re‑reasoning” overhead and allowing deeper collaborative planning.
- Localized Sovereign AI: Nations can fine‑tune the model on region‑specific language data while keeping the core architecture open.
For developers building AI agents, the AI marketing agents on UBOS already showcase how Nemotron 3 Super can power personalized campaign generation, content ideation, and real‑time performance analytics.
Key Features at a Glance
- 120 B parameters with Hybrid MoE for optimal compute‑efficiency.
- 7× higher throughput compared to previous Nemotron generations.
- 1 M token context window – ideal for long‑form reasoning.
- Multi‑Token Prediction reduces latency on complex prompts.
- Latent MoE compresses intermediate states, cutting memory use.
- NeMo RL‑Gym integration for agentic, reinforcement‑learning training.
- Full open‑source stack: weights, datasets, training scripts, and RL environments.
- Three quantization formats (BF16, FP8, NVFP4) for flexible deployment.
- Reasoning Budgets API: Full, Low‑Effort, and custom latency caps.
- Out‑of‑the‑box tool‑calling with support for 100+ functions.
Explore Related UBOS Resources
UBOS offers a suite of tools that complement Nemotron 3 Super’s capabilities:
- UBOS partner program – collaborate on AI solutions built on Nemotron 3 Super.
- Enterprise AI platform by UBOS – integrate the model into secure, scalable SaaS offerings.
- Workflow automation studio – design end‑to‑end pipelines that trigger Nemotron 3 Super for data extraction, analysis, and action.
- UBOS pricing plans – choose a cost‑effective tier for inference workloads.
- UBOS portfolio examples – see real‑world deployments of AI agents powered by large language models.
- UBOS templates for quick start – launch a “ChatGPT and Telegram integration” or “AI SEO Analyzer” in minutes.
For developers interested in voice‑enabled agents, the ElevenLabs AI voice integration pairs perfectly with Nemotron 3 Super’s tool‑calling to deliver spoken responses in real time.
Template Marketplace: Jump‑Start Your Projects
UBOS’s marketplace hosts dozens of ready‑made applications that can be powered by Nemotron 3 Super. A few standout templates include:
- AI SEO Analyzer – generate meta tags, keyword suggestions, and content outlines instantly.
- AI Article Copywriter – produce long‑form, SEO‑optimized articles with a single prompt.
- AI Video Generator – turn script text into short videos using text‑to‑video diffusion models.
- AI Chatbot template – create a conversational agent that can call external APIs via Nemotron 3 Super’s tool‑calling.
- AI LinkedIn Post Optimization – craft high‑engagement posts with data‑driven suggestions.
These templates are built on the Web app editor on UBOS, allowing you to customize UI, integrate additional APIs, and deploy to production with a single click.
Ready to Build the Next‑Generation AI Agent?
Dive deeper into Nemotron 3 Super, explore UBOS’s open‑source ecosystem, and start prototyping today. Whether you’re a startup, an SMB, or an enterprise, the combination of NVIDIA’s cutting‑edge LLM and UBOS’s low‑code platform accelerates AI innovation faster than ever.