NVIDIA

NVIDIA released Nemotron-Personas-Korea, a dataset containing 7 million demographically accurate synthetic personas grounded in official Korean statistics from KOSIS, Supreme Court of Korea, and the National Health Insurance Service. The dataset includes 26 fields per persona covering demographics, geography, and occupation across all 17 Korean provinces, with zero personally identifiable information under CC BY 4.0 license.

NVIDIA released GR00T N1.7, a 3-billion parameter open-source Vision-Language-Action model for humanoid robots with commercial licensing. The model was trained on 20,854 hours of human egocentric video data and demonstrates the first documented scaling law for robot dexterity, where increasing human video data from 1,000 to 20,000 hours more than doubles task completion rates.

NVIDIA has optimized Google's Gemma 4 models for local deployment on RTX and Spark platforms, targeting the emerging wave of on-device agentic AI. The optimization enables small, efficient models to access real-time local context for autonomous decision-making without cloud dependency.

MLCommons published MLPerf Inference v6.0 results on April 1, 2026, with Nvidia, AMD, and Intel each claiming top spots in different configurations. Nvidia's 288-GPU GB300-NVL72 system achieved 2.49 million tokens per second on DeepSeek-R1, while AMD's MI355X crossed one million tokens per second for the first time. Direct comparisons remain difficult as each chipmaker targets different market segments and benchmarks.

NVIDIA released gpt-oss-puzzle-88B on March 26, 2026, a 88-billion parameter mixture-of-experts model optimized for inference efficiency on H100 hardware. Built using the Puzzle post-training neural architecture search framework, the model achieves 1.63× throughput improvement in long-context (64K/64K) scenarios and up to 2.82× improvement on single H100 GPUs compared to its parent gpt-oss-120B, while matching or exceeding accuracy across reasoning effort levels.

NVIDIA released Nemotron-3-Nano-4B-GGUF on March 16, 2026, a 4-billion parameter small language model (SLM) designed for edge deployment on devices like Jetson Thor and GeForce RTX. The model features a hybrid Mamba-2 and Transformer architecture with a 262K token context window and supports both reasoning and non-reasoning modes via system prompts.

Nvidia has released Nemotron 3 Super, a 120-billion parameter hybrid Mamba-Transformer Mixture-of-Experts model that activates only 12 billion parameters during inference. The open-weight model features a 1-million token context window, multi-token prediction capabilities, and pricing at $0.10 per million input tokens and $0.50 per million output tokens.

NVIDIA Nemotron 3 Super, a hybrid Mixture of Experts model with 120B parameters and 12B active parameters, is now available as a fully managed model on Amazon Bedrock. The model supports up to 256K token context length and claims 5x higher throughput efficiency over the previous Nemotron Super and 2x higher accuracy on reasoning tasks.

NVIDIA released Nemotron 3 Content Safety 4B, an open-source multimodal safety model designed to moderate content across text, images, and multiple languages. Built on Gemma-3 4B-IT with a 128K context window, the model achieved 84% average accuracy on multimodal safety benchmarks and supports over 140 languages through culturally-aware training data.

Nvidia will invest $26 billion over the next five years to build open-weight AI models, according to a 2025 financial filing confirmed by executives. The move signals a strategic shift from chipmaker to AI frontier lab, with the company releasing Nemotron 3 Super (128B parameters) and claiming it outperforms GPT-OSS on multiple benchmarks.

An SEC filing reveals Nvidia plans to spend $26 billion on open-weight AI models over the next five years. The investment targets the open-source gap left by OpenAI, Meta, and Anthropic while countering the rise of Chinese open-source models and deepening developer dependence on Nvidia hardware.

NVIDIA has released Nemotron-3-Super-120B-A12B-NVFP4, a 120-billion parameter text generation model featuring a latent Mixture-of-Experts (MoE) architecture. The model supports 8 languages including English, French, Spanish, Italian, German, Japanese, and Chinese, and is available on Hugging Face with 8-bit quantization support through NVIDIA's ModelOpt toolkit.

NVIDIA has released Nemotron-3-Super-120B-A12B-BF16, a 120 billion parameter model designed for text generation and conversational tasks. The model employs a latent mixture-of-experts (MoE) architecture and supports multiple languages including English, French, Spanish, Italian, German, Japanese, and Chinese.

Nvidia and Thinking Machines Lab, founded by former OpenAI executive Mira Murati, have announced a long-term partnership. Details on the scope and terms of the collaboration remain limited.

Nvidia is preparing to launch an open-source AI agent platform, according to reports ahead of the company's annual developer conference. The move mirrors approaches by competitors like OpenAI in building agent-based AI systems.

Amazon Bedrock now offers NVIDIA's Nemotron 3 Nano as a fully managed serverless model, expanding its Nemotron portfolio alongside previously available Nemotron 2 Nano 9B and Nemotron 2 Nano VL 12B variants. The addition enables developers to deploy NVIDIA's smallest inference-optimized model without managing infrastructure.

Nvidia announced Monday it is investing $2 billion each into photonics companies Lumentum and Coherent to develop optical transceivers, circuit switches, and lasers for next-generation AI data centers. The technology aims to improve energy efficiency, data transfer speeds, and bandwidth in data center infrastructure.

Nvidia is reportedly planning a $30 billion investment in OpenAI, according to Reuters citing sources familiar with the matter. The deal would represent one of the largest funding commitments in the AI sector to date. Terms and timeline have not been officially confirmed by either company.