Model CoverageVision Language Models (VLMs)

Mistral-Small-4

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Mistral-Small-4-119B is Mistral AI’s multimodal MoE model supporting both text and image inputs at scale.

TaskImage-Text-to-Text
ArchitectureMistralForConditionalGeneration
Parameters119B (MoE)
HF Orgmistralai

Available Models

  • Mistral-Small-4-119B-Instruct-2512

Architecture

  • MistralForConditionalGeneration

Example HF Models

ModelHF ID
Mistral-Small-4 119B Instructmistralai/Mistral-Small-4-119B-Instruct-2512

Example Recipes

RecipeDatasetDescription
mistral4_medpix.yamlMedPix-VQASFT — Mistral-Small-4 on MedPix

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

This recipe was validated on 4 nodes × 8 GPUs (32 H100s). See the Launcher Guide for multi-node setup.

3. Run the recipe from inside the repo:

$automodel --nproc-per-node=8 examples/vlm_finetune/mistral4/mistral4_medpix.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/mistral4/mistral4_medpix.yaml

See the Installation Guide and VLM Fine-Tuning Guide.

Fine-Tuning

See the VLM Fine-Tuning Guide.

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