Ministral3 VL#

Ministral3 is Mistral AI’s efficient small model series. The vision-capable variants support image-text inputs for multimodal tasks.

Task

Image-Text-to-Text

Architecture

Mistral3ForConditionalGeneration

Parameters

3B – 14B

HF Org

mistralai

Available Models#

  • Ministral-3-14B-Instruct-2512

  • Ministral-3-8B-Instruct-2512

  • Ministral-3-3B-Instruct-2512

Architecture#

  • Mistral3ForConditionalGeneration

Example HF Models#

Model

HF ID

Ministral-3 3B Instruct

mistralai/Ministral-3-3B-Instruct-2512

Ministral-3 8B Instruct

mistralai/Ministral-3-8B-Instruct-2512

Ministral-3 14B Instruct

mistralai/Ministral-3-14B-Instruct-2512

Example Recipes#

Recipe

Dataset

Description

ministral3_3b_medpix.yaml

MedPix-VQA

SFT — Ministral3 3B on MedPix

ministral3_8b_medpix.yaml

MedPix-VQA

SFT — Ministral3 8B on MedPix

ministral3_14b_medpix.yaml

MedPix-VQA

SFT — Ministral3 14B 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

3. Run the recipe from inside the repo:

automodel --nproc-per-node=8 examples/vlm_finetune/mistral/ministral3_3b_medpix.yaml
Run with Docker

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:26.02.00

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/mistral/ministral3_3b_medpix.yaml

See the Installation Guide and VLM Fine-Tuning Guide.

Fine-Tuning#

See the VLM Fine-Tuning Guide.

Hugging Face Model Cards#