Nemotron 3 Nano 30B Model: https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16

In this video, I’ll be showing you NVIDIA’s new Nemotron 3 Nano and why it changes what we can expect from small, efficient models, with a hybrid Mamba + Transformer + MoE architecture that delivers strong reasoning, fast inference, and an enormous context window—while still being open and easy to try via an OpenAI-compatible API.

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Key Takeaways:

🚀 Nemotron 3 Nano aims to flip the “small models are dumb” narrative with better reasoning at high speed.
🧠 A hybrid architecture combines Mamba state-space layers with Transformer layers for efficient long-context handling.
🧩 The Mixture-of-Experts design is 30B parameters total, but only ~3B are active per token for low-latency inference.
🔓 It’s an open model with strong openness scoring, so you can inspect weights and run it yourself or use an API.
🔌 Works with OpenAI-compatible tooling, making setup simple with standard clients and minimal code changes.
🪑 Handles multi-constraint logic puzzles with “thinking” mode, mapping steps instead of guessing.
📄 Great for structuring messy text into clean JSON, with reasoning_budget to control latency vs. depth.
🗂️ The massive context window enables log analysis and long-document reasoning without the usual slowdown.
🛠️ NVIDIA’s NeMo Gym supports reinforcement-learning workflows for building specialized enterprise agents.
⚖️ Best for reasoning, routing, and data processing—less ideal for creative writing or building huge systems from scratch.

NVIDIA Nemotron 3 Nano 30B (A3B): This SMALL & OPEN Model is SO GOOD!