NVIDIA

A 30B total / 3B active parameter hybrid Mamba-2 + Transformer MoE language model built for efficient on-device and edge agentic tasks. It features a 1M-token context window, reasoning ON/OFF modes with configurable thinking budgets, and up to 4× faster throughput than its predecessor.

A 120B total / 12B active parameter hybrid Mamba-Transformer MoE language model with LatentMoE, multi-token prediction, and native NVFP4 pretraining. Optimized for complex multi-agent applications with a 1M-token context window and up to 5× higher throughput than the previous Nemotron Super.

A 4B-parameter multimodal, multilingual small language model designed as a robust content-safety moderator. It supports standard taxonomy safety classification and custom-policy enforcement with reasoning traces for text and image inputs.