NVIDIA releases Nemotron-3-Super-120B, a 120B parameter model with latent MoE architecture
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.
Nemotron 3 Super — Quick Specs
NVIDIA has released Nemotron-3-Super-120B-A12B-NVFP4, a 120-billion parameter model designed for conversational text generation with support for multiple languages.
Model Specifications
The model implements a latent Mixture-of-Experts (MoE) architecture, which reduces computational overhead during inference compared to standard dense models of equivalent scale. The NVFP4 designation indicates the model uses NVIDIA's custom floating-point quantization format.
Language support includes English, French, Spanish, Italian, German, Japanese, and Chinese, positioning the model for multilingual deployment scenarios.
Training and Development
According to NVIDIA's documentation, the model was trained using the Nemotron post-training (v3) and pre-training datasets. Two research papers accompany the release: arxiv:2512.20848 and arxiv:2512.20856, providing technical details on the training methodology and architecture decisions.
The model card indicates training data cutoff in December 2025.
Technical Capabilities
Nemotron-3-Super-120B is optimized for conversational tasks and text generation workloads. The model supports 8-bit quantization through NVIDIA's ModelOpt optimization toolkit, enabling deployment on hardware with reduced memory requirements. It is compatible with standard transformer inference endpoints.
The model is released under a custom license (non-standard open-source terms), requiring review of NVIDIA's specific licensing terms before use.
Availability
The model is available on Hugging Face with 11,460+ downloads as of the release date and 73 likes from the community. It is compatible with the transformers library using safetensors format and includes custom code components.
NVIDIA has marked the model as US-region eligible, suggesting potential regulatory or distribution considerations.
What This Means
Nemotron-3-Super-120B represents NVIDIA's continued push into open-weight model releases, competing directly with Meta's Llama series and other 120B-scale models. The latent MoE architecture is noteworthy—by concentrating sparsity in the architecture rather than parameter count, NVIDIA claims efficiency gains without sacrificing model capacity. For organizations evaluating 120B-scale models, the multilingual support and native NVIDIA optimization tooling make this a viable alternative to existing open-weight options, though the custom license requires careful legal review for commercial use.
Related Articles
Moonshot AI Releases Kimi K3: Open-Weight 2.8T-Parameter Model With 1M-Token Context and Native Multimodality
Moonshot AI has released Kimi K3, an open-weight 2.8-trillion-parameter mixture-of-experts model with 104B activated parameters, a 1,048,576-token context window, and native multimodal support. The company describes it as the world's first open 3T-class model, built on a new Kimi Delta Attention architecture.
InclusionAI Releases Ling-3.0-flash, a 124B MoE Model with 5.1B Active Parameters
InclusionAI has released Ling-3.0-flash, a 124-billion-parameter Mixture-of-Experts model that activates roughly 5.1 billion parameters per token. The model targets production-scale agentic workloads with a 262K context window and an emphasis on token efficiency.
Microsoft Launches MAI-Cyber-1-Flash Security Model, Still Routes Hard Cases to OpenAI's GPT-5.4
Microsoft has released MAI-Cyber-1-Flash, a compact cybersecurity model built into its MDASH multi-agent system that scores 96 percent on the CyberGym benchmark. The setup handles 90 percent of security tasks in-house but still hands off difficult cases to OpenAI's GPT-5.4.
Microsoft Launches MAI-Cyber-1-Flash, Its First Cybersecurity Model, With Agentic Security Platform Perception
Microsoft has launched MAI-Cyber-1-Flash, its first cybersecurity-specialized model, alongside Perception, an agentic platform for automated threat detection and remediation. The company claims the model outperforms rivals from Anthropic, Google and OpenAI on the Cyber Gym benchmark, though no independent scores have been published.
Comments
Loading...