Nemotron-3-Nano-Omni-30B-A3B-Reasoning-NVFP4 news
14 articles mentioning Nemotron-3-Nano-Omni-30B-A3B-Reasoning-NVFP4
How to Fine-Tune Nemotron 3.5 ASR for Your Language, Domain, or Accent
Task-Seeded Synthetic Q&A Generation for Nemotron Pretraining
Towards Speed-of-Light Text Generation with Nemotron-Labs Diffusion Language Models
Nemotron 3 Nano Omni: Efficient and Open Multimodal Intelligence
arXiv:2604.24954v2 Announce Type: replace-cross Abstract: We introduce Nemotron 3 Nano Omni, the latest model in the Nemotron multimodal series and the first to natively support audio inputs alongside text, images, and video. Nemotron 3 Nano Omni delivers consistent accuracy improvements over its pr
Introducing NVIDIA Nemotron 3 Nano Omni: Long-Context Multimodal Intelligence for Documents, Audio and Video Agents
Accelerating PayPal's Commerce Agent with Speculative Decoding: An Empirical Study on EAGLE3 with Fine-Tuned Nemotron Models
arXiv:2604.19767v1 Announce Type: new Abstract: We evaluate speculative decoding with EAGLE3 as an inference-time optimization for PayPal's Commerce Agent, powered by a fine-tuned llama3.1-nemotron-nano-8B-v1 model. Building on prior work (NEMO-4-PAYPAL) that reduced latency and cost through domain-
Nemotron 3 Super: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning
arXiv:2604.12374v1 Announce Type: cross Abstract: 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-
Nemotron-Cascade: Scaling Cascaded Reinforcement Learning for General-Purpose Reasoning Models
arXiv:2512.13607v2 Announce Type: replace-cross Abstract: Building general-purpose reasoning models with reinforcement learning (RL) entails substantial cross-domain heterogeneity, including large variation in inference-time response lengths and verification latency. Such variability complicates the