
Nemotron 3 Nano Omni Unifies Vision, Audio, Language
NVIDIA's new open omni model activates 3B of 30B parameters, processes video, audio, and documents in one pass, and delivers up to 9.2x higher throughput than other open omni models.
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NVIDIA's new open omni model activates 3B of 30B parameters, processes video, audio, and documents in one pass, and delivers up to 9.2x higher throughput than other open omni models.

NVIDIA's first open omni-modal model: 30B total / 3B active hybrid Mamba-MoE that processes text, images, audio, and video in a single inference loop, with 9x higher throughput than comparable open omni models.

NVIDIA Nemotron 3 Super is the strongest open-weight model for agentic coding as of March 2026, but its efficiency-first design means real trade-offs on general knowledge and chat quality.

NVIDIA's new Nemotron-Cascade-2-30B-A3B activates just 3B parameters per token, runs on a single RTX 4090, and outscores NVIDIA's own 120B model on coding and math benchmarks.

NVIDIA's Nemotron 3 Nano 4B packs a Mamba-dominant hybrid architecture, 262K token context, and 95.4% on MATH500 into a model that fits an 8GB Jetson Orin Nano.

Mistral AI releases Small 4 - a 119B MoE with only 6B active parameters, 256K context, configurable reasoning, and Apache 2.0 license. Plus a new NVIDIA partnership to co-develop frontier open models.

NVIDIA Nemotron 3 Super is a 120B-parameter open model with 12B active at inference, combining Mamba-2, LatentMoE, and Multi-Token Prediction for agentic workloads with a 1M token context window.

NVIDIA releases Nemotron 3 Super, a 120B-parameter open model with only 12B active at inference, combining Mamba-2 and Transformer layers for agentic AI workloads with a 1M token context window.

Comparing Moonshot AI's trillion-parameter Kimi K2.5 with NVIDIA's Mamba2-MoE hybrid Nemotron 3 Nano 30B-A3B - frontier intelligence versus a model engineered for maximum throughput, 1M context, and 10x lower cost.

NVIDIA's hybrid Mamba2+MoE model packs 31.6B total parameters but activates only 3.2B per token, delivering frontier-class reasoning with 3.3x the throughput of comparable models on a single H200 GPU.

A data-driven comparison of Alibaba's Qwen3.5-35B-A3B and NVIDIA's Nemotron 3 Nano 30B-A3B - two ~30B MoE models activating ~3B parameters that take fundamentally different architectural approaches to the same problem.