Uploaded February 2026 | Updated September 2026, 2 weeks ago
Curious how Nemotron 3 Nano was built—and how to start building agents with Nemotron 3 Nano? Nemotron 3 Nano is an open, hybrid Mamba‑Transformer MoE model designed for efficient, long‑context agentic workloads. This livestream is your chance to chat directly with the Nemotron AI researchers behind the model and learn what’s new.
In this Nemotron Labs livestream, you can ask about:
- How the hybrid Mamba‑Transformer MoE backbone works in practice, and what it means for latency, throughput, and long‑range reasoning in real‑world agents.
- How multi‑environment reinforcement learning and the 1M‑token context length help with multi‑document reasoning, long‑running memory, and tool‑using workflows.
- What’s actually in the open training pipeline—data, weights, and recipes—and how to get Nemotron 3 Nano running quickly using the public cookbooks and examples.
Don’t miss your chance to learn from NVIDIA AI research experts. No prior expertise required—join the stream and come ready with your questions!
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Resources:
Nemotron 3 Nano NVFP4 Blog → nvda.ws/4abOPgC
Nemotron 3 Nano NVFP4 HuggingFace → nvda.ws/3On4QsQ
NVIDIA Model Optimizer → nvda.ws/4ryTO2g
Nemotron 3 Nano on HuggingFace → nvda.ws/3OkWTV6
Access more NVIDIA Nemotron developer resources and join our developer community:
⬇️ Developer Resources → nvda.ws/425fFUJ
📚 Explore Models & Datasets → nvda.ws/4n9Ad6N
👥 Join the Community → nvda.ws/46Rxucr
💻 Visit the Nemotron Discord channel→nvda.ws/421EzEC
📧Email us directly → community@nvidia.com
▶️ Watch Tutorials & Livestreams → nvda.ws/4n5WrXo
Get Started with Learning Paths:
Build an AI Agent → nvda.ws/3LB3QAf
Build a RAG Agent → nvda.ws/4nV0wNz
Curious how Nemotron 3 Nano was built—and how to start building agents with Nemotron 3 Nano? Nemotron 3 Nano is an open, hybrid Mamba‑Transformer MoE model designed for efficient, long‑context agentic workloads. This livestream is your chance to chat directly with the Nemotron AI researchers behind the model and learn what’s new.
In this Nemotron Labs livestream, you can ask about:
- How the hybrid Mamba‑Transformer MoE backbone works in practice, and what it means for latency, throughput, and long‑range reasoning in real‑world agents.
- How multi‑environment reinforcement learning and the 1M‑token context length help with multi‑document reasoning, long‑running memory, and tool‑using workflows.
- What’s actually in the open training pipeline—data, weights, and recipes—and how to get Nemotron 3 Nano running quickly using the public cookbooks and examples.
Don’t miss your chance to learn from NVIDIA AI research experts. No prior expertise required—join the stream and come ready with your questions!
----------
Resources:
Nemotron 3 Nano NVFP4 Blog → nvda.ws/4abOPgC
Nemotron 3 Nano NVFP4 HuggingFace → nvda.ws/3On4QsQ
NVIDIA Model Optimizer → nvda.ws/4ryTO2g
Nemotron 3 Nano on HuggingFace → nvda.ws/3OkWTV6
Access more NVIDIA Nemotron developer resources and join our developer community:
⬇️ Developer Resources → nvda.ws/425fFUJ
📚 Explore Models & Datasets → nvda.ws/4n9Ad6N
👥 Join the Community → nvda.ws/46Rxucr
💻 Visit the Nemotron Discord channel→nvda.ws/421EzEC
📧Email us directly → community@nvidia.com
▶️ Watch Tutorials & Livestreams → nvda.ws/4n5WrXo
Get Started with Learning Paths:
Build an AI Agent → nvda.ws/3LB3QAf
Build a RAG Agent → nvda.ws/4nV0wNz
