NVIDIA

Nvidia has released Nemotron 3 Ultra, a 550-billion parameter mixture-of-experts model with 55 billion active parameters and support for up to 1 million token context windows. The model uses a hybrid Transformer-Mamba architecture and is designed specifically for long-running agentic workflows including agent orchestration, coding agents, and complex enterprise tasks.

NVIDIA released Nemotron-3-Ultra-550B-A55B-NVFP4, a 550B parameter model with 55B active parameters, featuring a 1M token context window and configurable reasoning mode. The model uses a hybrid LatentMoE architecture combining Mamba-2, Mixture-of-Experts, and Attention layers with Multi-Token Prediction, trained with NVIDIA's NVFP4 quantization-aware approach.

NVIDIA released Nemotron-3-Ultra-550B, a frontier-scale model with 550B total parameters (55B active) and up to 1M token context window. The model uses a hybrid LatentMoE architecture combining Mamba-2, MoE, and attention layers with Multi-Token Prediction, trained with NVFP4 quantization-aware methods from December 2025 to April 2026.

NVIDIA has released Nemotron 3.5 Content Safety, a 4B-parameter model built on Google Gemma 3 4B IT that provides multimodal safety classification across approximately 140 languages. The model includes a 128K context window, custom enterprise policy enforcement, auditable reasoning traces, and is releasing its training dataset.

NVIDIA Nemotron 3 Ultra is now available on Amazon SageMaker JumpStart with 550 billion total parameters and 55 billion active parameters. The model features a hybrid Transformer-Mamba Mixture-of-Experts architecture and supports context windows up to 1 million tokens, targeting agentic AI workloads.

Nvidia has released Nemotron 3.5 Content Safety, a 4-billion parameter multimodal guardrail model fine-tuned from Google Gemma-3-4B. The model is available for free, supports 128K token context windows, and moderates content across 12 languages.

Nvidia has released Nemotron 3 Ultra, a 550B parameter mixture-of-experts model with 55B active parameters and a 1M token context window. The model uses a hybrid Transformer-Mamba architecture and is available for free through OpenRouter, targeting agentic workflows and multi-step reasoning tasks.

NVIDIA released Nemotron 3.5 ASR, a 600M-parameter speech-to-text model supporting 40 language-locales from a single checkpoint. The model achieves 0.07 seconds to final transcript after speech ends and ranks 2nd in latency among streaming ASR models according to Artificial Analysis benchmarks.

NVIDIA demonstrated that task-seeded synthetic Q&A data improves model performance across multiple benchmarks in a 100B-token continuation experiment on Nemotron-3 Nano. The approach improved GPQA scores by +11.1 points, MMLU-Pro by +1.8, average code by +1.9, and commonsense understanding by +1.6.

NVIDIA released Cosmos3-Super-Text2Image, a 64-billion parameter text-to-image generation model as part of its Cosmos3 collection of omnimodal world models. The model uses a Mixture-of-Transformers architecture combining autoregressive and diffusion transformers, designed for Physical AI applications including robotics and autonomous vehicles.

NVIDIA released Cosmos 3, an omnimodal world foundation model platform for Physical AI spanning robotics, autonomous driving, and industrial environments. The flagship Cosmos3-Super variant contains 64 billion parameters and generates video, images, audio, and action commands from text, image, video, and action trajectory inputs using a Mixture-of-Transformers architecture.

NVIDIA released Cosmos3-Super, a 64-billion parameter omnimodal foundation model that generates video, images, audio, and action commands from combinations of text, image, video, and action trajectory inputs. The model, part of the Cosmos3 collection, targets Physical AI applications including robotics, autonomous vehicles, and industrial automation.

NVIDIA has released Cosmos3-Nano, a 16-billion parameter omnimodal world model capable of generating video, audio, images, and robot action commands from combinations of text, image, video, and action trajectory inputs. The model supports a 256K token context window and is designed for Physical AI applications including robotics, autonomous vehicles, and smart manufacturing environments.

NVIDIA has released Cosmos 3, a unified omni-model that combines world generation, physical reasoning, and action generation in a single architecture. Available in 8B (Nano) and 32B (Super) parameter versions on Hugging Face, Cosmos 3 uses a Mixture-of-Transformers architecture to process text, image, video, audio, and action modalities without switching between separate models.

NVIDIA released LocateAnything-3B, a 3-billion parameter vision-language model that predicts bounding boxes in parallel rather than token-by-token, achieving up to 2.5× higher throughput compared to autoregressive approaches. The model, trained on 12M images with 138M+ queries and 785M bounding boxes, supports object detection, GUI element grounding, and robotics perception.

NVIDIA has released Nemotron-Labs Diffusion, a family of diffusion language models at 3B, 8B, and 14B scales that generate multiple tokens in parallel rather than one at a time. The 8B model achieves 6.4× higher tokens per forward pass than autoregressive models in self-speculation mode while maintaining comparable accuracy.

NVIDIA released Nemotron-Labs-Diffusion-14B, a 14-billion parameter language model that supports three decoding modes by switching attention patterns during inference. The model achieves 850 tokens per second on GB200 hardware at concurrency 1, representing a 3.3x speed-up over standard autoregressive decoding and outperforming Qwen3-8B-Eagle3 by 2.2x in self-speculation mode.

NVIDIA published a technical guide for parameter-efficient fine-tuning of its Cosmos Predict 2.5 world model using LoRA and DoRA adapters. The method allows teams to adapt the 2B-parameter model to robot manipulation tasks on a single 80GB GPU, generating synthetic training trajectories from just 92 demonstration videos.

NVIDIA released Nemotron-3-Nano-Omni-30B-A3B, a multimodal large language model with 31 billion parameters that processes video, audio, images, and text with up to 256K token context. The model uses a Mamba2-Transformer hybrid Mixture of Experts architecture and supports chain-of-thought reasoning mode.

NVIDIA released Nemotron 3 Nano Omni, a 31B parameter (30B active, 3B per token) multimodal model supporting video, audio, image, and text inputs. The model features a 256K token context window, reasoning mode with chain-of-thought, and tool calling capabilities.