Instructions to use luiscalisto/Mistral-Small-3.1-24B-Instruct-2503-MLX-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use luiscalisto/Mistral-Small-3.1-24B-Instruct-2503-MLX-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Mistral-Small-3.1-24B-Instruct-2503-MLX-4bit luiscalisto/Mistral-Small-3.1-24B-Instruct-2503-MLX-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
Mistral-Small-3.1-24B-Instruct-2503-MLX-4bit
MLX 4-bit quantisation of mistralai/Mistral-Small-3.1-24B-Instruct-2503,
converted for use on Apple Silicon via mlx-vlm.
Source model
- Repository:
mistralai/Mistral-Small-3.1-24B-Instruct-2503 - Release: 2025-03
- Family: mistral
- Origin: eu
- Languages / coverage: 24+ languages incl. all major EU languages; vision-language model (image + text input)
- License: apache-2.0 (inherited)
Notes from upstream
Mistral AI (France). Multimodal: mistral3 architecture with a Pixtral vision encoder. Converted with mlx-vlm (not mlx-lm) so the language model, vision tower and multi_modal_projector are quantised consistently with current mlx-vlm loaders. Older community 4-bit uploads that predate the affine quantisation mode fail to load under mlx-vlm 0.5.0.
Conversion details
- Tool:
mlx-vlm0.5.0 - Quantisation: 4-bit (defaults from
mlx_vlm.convert) - Converted on: 2026-05-22
Usage
from mlx_vlm import load, generate
from mlx_vlm.prompt_utils import apply_chat_template
from mlx_vlm.utils import load_config
model, processor = load("luiscalisto/Mistral-Small-3.1-24B-Instruct-2503-MLX-4bit")
config = load_config("luiscalisto/Mistral-Small-3.1-24B-Instruct-2503-MLX-4bit")
image = ["path/to/image.jpg"]
prompt = apply_chat_template(processor, config, "Describe this image.", num_images=len(image))
print(generate(model, processor, prompt, image, max_tokens=128, verbose=False))
License and attribution
This is a quantised redistribution of mistralai/Mistral-Small-3.1-24B-Instruct-2503. The original model and
its license terms (apache-2.0) carry through unchanged. Please cite the
upstream authors when using this model. See the source repository for the
authoritative model card and citation.
Conversion provenance
Produced by llm-mlx-conversions,
a small utility for publishing community MLX 4-bit quants of open-weight LLMs.
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Model tree for luiscalisto/Mistral-Small-3.1-24B-Instruct-2503-MLX-4bit
Base model
mistralai/Mistral-Small-3.1-24B-Base-2503