NVIDIA PhysicsNeMo: open-source Physics-ML deep learning framework
NVIDIA has published PhysicsNeMo, an open-source Python framework for building, training, and fine-tuning deep learning models using Physics-ML methods. The repository has accumulated 2,933 stars on GitHub. Physics-informed ML is a growing area relevant to scientific computing and simulation workloads.
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NVIDIA NeMo Gym: framework for evaluating and improving models and agents using environments
NVIDIA's NeMo team has published a Python library called NeMo Gym on GitHub, designed to evaluate and improve models and agents through environment-based interaction. The repository has 941 stars with minimal recent traction (+1 today). It appears to be an RL-style evaluation and training harness within the NeMo ecosystem.
Measuring Open-Source Llama Nemotron Models on DeepResearch Bench
NVIDIA evaluates its open-source Llama Nemotron models on the DeepResearch Bench, a benchmark designed to assess deep research agent capabilities. The post appears to report competitive performance of the Nemotron models in agentic research tasks. This is relevant to the ongoing development of open-weights models capable of multi-step research and reasoning workflows.
Nvidia Nemotron 3 Ultra: hybrid Mamba-transformer open-weights model targeting agentic workloads
Nvidia released Nemotron 3 Ultra, a 550B parameter (55B active) hybrid Mamba-transformer mixture-of-experts model with a 1M token context window, publishing weights, training data, and RL environments under an open license. The model ranks as the highest-scoring U.S. open-weights model on the Artificial Analysis Intelligence Index (47.7-48.2) and is approximately three times faster than comparable open-weights rivals, though it trails leading Chinese models like Kimi K2.6 and DeepSeek V4 Pro on intelligence benchmarks. Nvidia used a novel Multi-Teacher On-Policy Distillation approach with 10+ specialized teacher models and trained using NVFP4 quantization. The release is strategically motivated by Nvidia's interest in a healthy open-weights ecosystem that drives AI semiconductor adoption.
Nvidia releases Nemotron 3 Super 120B-A12B open-weights model with hybrid Mamba-2/MoE architecture
Nvidia released Nemotron 3 Super 120B-A12B, an open-weights LLM with a hybrid Mamba-2/transformer/MoE architecture that activates only 12B parameters per token and supports up to 1 million token context. The model claims the fastest inference speed in its size class at 442 tokens/second and leads open-weights models on PinchBench agentic task evaluation, outperforming larger models including Kimi K2.5 (1T parameters). Nvidia is releasing weights, training data, and recipes under a permissive commercial license, and plans a $26B five-year investment in open-weights models — framed partly as a strategic response to Chinese labs building capable open-weights models on non-Nvidia hardware.
The Open Evaluation Standard: Benchmarking NVIDIA Nemotron 3 Nano with NeMo Evaluator
NVIDIA and Hugging Face present an evaluation methodology for the Nemotron 3 Nano model using the NeMo Evaluator framework. The post describes benchmark results and an open evaluation recipe intended to standardize how small/nano-scale models are assessed. It positions NeMo Evaluator as a reproducible, open evaluation stack for the community.
Mistral AI Highlights Physics AI Research Portfolio Following Emmi AI Acquisition
Mistral AI has published a research overview showcasing Physics AI work stemming from its acquisition of Emmi AI, targeting industrial engineering domains including aerospace, automotive, semiconductors, and energy. The portfolio spans neural surrogate models for CFD simulations, plasma turbulence modeling for nuclear fusion, and universal physics transformers capable of handling large-scale multi-physics processes. Key published works include AB-UPT (Anchored-Branched Universal Physics Transformer), NeuralDEM, UPT, and GyroSwin, several with open-source code. The announcement signals Mistral's strategic push into scientific and industrial AI beyond language modeling.
Welcome NVIDIA Cosmos 3: The First Open Omni-model for Physical AI Reasoning and Action
NVIDIA has released Cosmos 3, described as the first open omni-model targeting physical AI reasoning and action. The model is hosted and announced via Hugging Face, positioning it as an open-weights offering for robotics and embodied AI applications. The announcement highlights multimodal capabilities oriented toward physical world understanding and agent-level action.
NVIDIA Llama Nemotron Nano VLM Released on Hugging Face Hub
NVIDIA has released the Llama Nemotron Nano VLM on Hugging Face Hub, a compact vision-language model built on the Llama architecture. The model is part of NVIDIA's Nemotron family targeting efficient multimodal inference. This release makes the model accessible to the broader research and developer community through Hugging Face's model hosting infrastructure.