About this model
NVIDIA Nemotron 3 Nano 30B-A3B is a compact Mixture-of-Experts language model in the Nemotron 3 family, trained from scratch by NVIDIA and designed as a unified system for both reasoning and non-reasoning tasks. It first generates a reasoning trace and then concludes with a final response, targeting developers building AI agents, chatbots, and retrieval-augmented systems. Architecturally, it pairs a hybrid Mamba-2 and Transformer backbone with sparse MoE feed-forward layers, activating just 3.2B of its 31.6B total parameters per forward pass.
Against its same-family predecessor, NVIDIA states Nemotron 3 Nano achieves better accuracy than the previous-generation Nemotron 2 Nano while activating less than half the parameters per forward pass. NVIDIA positions the model for high inference throughput on a single H200 GPU at an 8K-input/16K-output setting.
The model supports context up to 1M tokens, though deployment defaults and VRAM constraints often run it at 256k; this catalog entry exposes a 128k window with FP8 quantization. Training data covers webpages, dialogue, and articles in English, 19 additional languages, and 43 programming languages.
Within Venice's NVIDIA lineup, Nemotron 3 Nano sits alongside the later Nemotron Cascade 2 30B A3B text model, the Nemotron Embed VL 1B v2 embedding model, and the [[sibling:nvidia/parakeet-tdt-0.6b-v3|Parakeet ASR]] speech model. NVIDIA released the weights, training recipe, and redistributable data openly.
This About section is AI-generated from public sources (Claude Opus 4.8), with no human editing. It may contain inaccuracies — verify critical details against the sources listed above.
Data sources: Venice API · HuggingFace · Wikipedia — enrichment updated 1d ago