Ministral3 / Devstral#

Ministral is Mistral AI’s efficient small model series optimized for on-device and edge use cases. Devstral is a code-focused model built on the same architecture, designed for software engineering agents.

Both use the Mistral3ForConditionalGeneration architecture.

Task

Text Generation

Architecture

Mistral3ForConditionalGeneration

Parameters

3B – 24B

HF Org

mistralai

Available Models#

Ministral3:

  • Ministral-3-3B-Instruct-2512

  • Ministral-3-8B-Instruct-2512

  • Ministral-3-14B-Instruct-2512

Devstral:

  • Devstral-Small-2-24B-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

Devstral Small 2 24B

mistralai/Devstral-Small-2-24B-Instruct-2512

Example Recipes#

Recipe

Description

devstral2_small_2512_squad.yaml

SFT — Devstral Small 2 24B on SQuAD

devstral2_small_2512_squad_peft.yaml

LoRA — Devstral Small 2 24B on SQuAD

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/llm_finetune/devstral/devstral2_small_2512_squad.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/llm_finetune/devstral/devstral2_small_2512_squad.yaml

See the Installation Guide and LLM Fine-Tuning Guide.

Fine-Tuning#

See the LLM Fine-Tuning Guide.

Hugging Face Model Cards#