Model CoverageOmni Models

Qwen3-Omni

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Qwen3-Omni is Alibaba Cloud’s omnimodal model supporting text, image, audio, and video inputs in a single unified architecture with a MoE language backbone.

TaskOmnimodal (Text·Image·Audio·Video)
ArchitectureQwen3OmniForConditionalGeneration
Parameters30B total / 3B active
HF OrgQwen

Available Models

  • Qwen3-Omni-30B-A3B: 30B total, 3B activated (MoE)

Architecture

  • Qwen3OmniForConditionalGeneration

Example HF Models

ModelHF ID
Qwen3-Omni 30B A3BQwen/Qwen3-Omni-30B-A3B

Example Recipes

RecipeDatasetDescription
qwen3_omni_moe_30b_te_deepep.yamlMedPix-VQASFT — Qwen3-Omni 30B with TE + DeepEP

Try with NeMo AutoModel

1. Install (full instructions):

$pip install nemo-automodel

2. Clone the repo to get the example recipes:

$git clone https://github.com/NVIDIA-NeMo/Automodel.git
$cd Automodel

3. Run the recipe from inside the repo:

$automodel --nproc-per-node=8 examples/vlm_finetune/qwen3/qwen3_omni_moe_30b_te_deepep.yaml

1. Pull the container and mount a checkpoint directory:

$docker run --gpus all -it --rm \
>  --shm-size=8g \
>  -v $(pwd)/checkpoints:/opt/Automodel/checkpoints \
>  nvcr.io/nvidia/nemo-automodel:26.04.00

2. Navigate to the AutoModel directory (where the recipes are):

$cd /opt/Automodel

3. Run the recipe:

$automodel --nproc-per-node=8 examples/vlm_finetune/qwen3/qwen3_omni_moe_30b_te_deepep.yaml

See the Installation Guide and Omni Fine-Tuning Guide.

Fine-Tuning

See the VLM / Omni Fine-Tuning Guide.

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