Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16

by nvidia

Omnimodal VLM that processes text, images, video, and audio with only 3B active parameters

263Kdl/month

31B total / 3B activeparams

HuggingFace Run on your data, free

Identifiers

Model ID

nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16

Feature URI

mixpeek://image_extractor@v1/nvidia_nemotron3_nano_omni_v1

Overview

Nemotron-3-Nano-Omni is NVIDIA's Mixture-of-Experts model that unifies vision, audio, and language understanding in a single architecture. With 31B total parameters but only 3B active per token, it delivers omnimodal perception at a fraction of the compute cost of dense models — up to 9x throughput over comparable open alternatives.

On Mixpeek, Nemotron-3-Nano-Omni serves as a universal perception backbone: a single model call extracts understanding from video (up to 2 minutes), audio (up to 1 hour), images, and text. This eliminates the need for separate caption, transcription, and analysis models in complex pipelines.

Architecture

Mamba2-Transformer hybrid MoE. C-RADIOv4-H vision encoder + Parakeet-TDT-0.6B audio encoder + MoE language decoder. 31B total / ~3B active params per token. 256K context window. Processes up to 2 minutes of video or 1 hour of audio.

Mixpeek SDK Integration

import { Mixpeek } from "mixpeek";

const mx = new Mixpeek({ apiKey: "API_KEY" });

// Managed: create a collection over a bucket; Mixpeek runs this model's extractor
const collection = await mx.collections.create({
  namespace_id: "my-namespace",
  collection_name: "my-collection",
  source: { type: "bucket", bucket_ids: ["bkt_your_bucket"] },
  feature_extractor: {
    feature_extractor_name: "scene_caption",
    version: "v1",
    parameters: { model_id: "nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16" },
  },
});

Capabilities

Unified vision + audio + text understanding in one model
Only 3B active parameters per token (MoE efficiency)
256K context window for long audio and document processing
Strong OCR and document understanding (67.04 on OCRBenchV2)
Video + audio QA (74.52 on DailyOmni)

Use Cases on Mixpeek

Universal content understanding: caption, transcribe, and analyze in one pass

Video Q&A: answer questions about visual and audio content simultaneously

Meeting analysis: understand slides, speaker audio, and chat simultaneously

Multi-format content indexing: process mixed media without separate models

Benchmarks

Dataset	Metric	Score	Source
Video MME	Accuracy	72.2%	NVIDIA, 2026 — arxiv:2604.24954
DailyOmni (video+audio QA)	Accuracy	74.52%	NVIDIA, 2026 — arxiv:2604.24954
OCRBenchV2 (EN)	Accuracy	67.04	NVIDIA, 2026 — arxiv:2604.24954