---
title: "OmniVinci"
description: "OmniVinci from NVIDIA: multimodal-reasoning and audio-reasoning; Runner parity pending."
modelId: "omnivinci"
pageSource: generated
---

OmniVinci is NVIDIA's omni-modal understanding LLM: one model that reasons over images, video, and audio together. In this catalog it is an understanding/reasoning entry, not a generator — tasks are multimodal reasoning, audio reasoning, and image/video question answering, and the artifact is a model_response.

<ModelPaperFigures modelId="omnivinci" locale="en" />

Code: [nvidia/omnivinci](https://huggingface.co/nvidia/omnivinci).

<ModelCommandBuilder modelId="omnivinci" locale="en" />

## What it is for

Pick `omnivinci` for the recorded multimodal reasoning route: documented inputs in, a reasoning artifact out. Use it when the card is a reasoner, not a generator.

NVIDIA describes OmniVinci as an omni-modal LLM with joint vision-audio alignment (public release at nvidia/omnivinci). This repository records the prompt/image/video input contract; parameter counts and internals are not recorded here.

Catalog tasks include multimodal-reasoning, audio-reasoning, image-question-answering, and video-question-answering. Catalog aliases include `nvidia/omnivinci`.

## Runtime contract

Optional `prompt`, `image`, `video`, `seed`, and `frames`; artifacts `omnivinci.json`.

CLI task profiles: `multimodal-reasoning`, `audio-reasoning`, `image-question-answering`, `video-question-answering`, and `video_generation`. WorldFoundry binds `OmniVinciPipeline`.

Family status: **Runner parity pending**.

Use it to interrogate videos produced by generation entries — e.g. asking questions about physical plausibility or event order — rather than to generate content.

WorldFoundry route is complete; missing checkpoint/assets are reported at runtime.

## Running in WorldFoundry

Launch `worldfoundry-eval run omnivinci --pipeline.task-profile multimodal-reasoning` to run the reasoning route. The command builder above switches `--pipeline.task-profile` among recorded tasks and still emits `worldfoundry-eval run`.

It runs in the unified environment `worldfoundry-unified-cu128` (Python 3.11, CUDA 12.8).

Recorded weight repositories include `nvidia/omnivinci`. Prepare the environment and check local assets with `bash scripts/inference/prepare_model_infer.sh omnivinci`. Add `--download` to fetch missing public checkpoints.

Status: **Runner parity pending**.

<ModelRelatedRecipes modelId="omnivinci" locale="en" />