Nemotron 3 Super: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning
We describe the pre-training, post-training, and quantization of Nemotron 3 Super, a 120 billion (active 12 billion) parameter hybrid Mamba-Attention Mixture-of-Experts model. Nemotron 3 Super is the first model in the Nemotron 3 family to 1) be pre-trained in NVFP4, 2) leverage LatentMoE, a new Mixture-of-Experts architecture that optimizes for both accuracy per FLOP and accuracy per parameter, and 3) include MTP layers for inference acceleration through native speculative decoding. We pre-trained Nemotron 3 Super on 25 trillion tokens followed by post-training using supervised fine tuning (SFT) and reinforcement learning (RL). The final model supports up to 1M context length and achieve...
| Authors | NVIDIA, :, Aakshita Chandiramani et al. |
|---|---|
| Primary category | cs.LG |
| Published | 14 April 2026 |
| Last updated at source | 14 April 2026 |
Connected in the knowledge graph
- danielrmay/NVIDIA-Nemotron-Labs-3-Puzzle-75B-A9B-W4A16Model · cited by
- nvidia/NVIDIA-Nemotron-Labs-3-Puzzle-75B-A9B-BF16Model · cited by
- nvidia/NVIDIA-Nemotron-Labs-3-Puzzle-75B-A9B-NVFP4Model · cited by
- nvidia/NVIDIA-Nemotron-Labs-3-Puzzle-75B-A9B-FP8Model · cited by
Models and datasets referencing this paper
Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.