Text Generation
MLX
Safetensors
English
French
mistral3
mlx-lm
mistral
apple-silicon
quantized
4-bit precision
Instructions to use TyKaoz/Mistral-Small-3.2-24B-Instruct-2506-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use TyKaoz/Mistral-Small-3.2-24B-Instruct-2506-4bit with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("TyKaoz/Mistral-Small-3.2-24B-Instruct-2506-4bit") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use TyKaoz/Mistral-Small-3.2-24B-Instruct-2506-4bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "TyKaoz/Mistral-Small-3.2-24B-Instruct-2506-4bit" --prompt "Once upon a time"
Configuration Parsing Warning:Config file tokenizer_config.json cannot be fetched (too big)
Mistral Small 3.2 24B Instruct โ 4-bit MLX
4-bit MLX quantization of
mistralai/Mistral-Small-3.2-24B-Instruct-2506, for Apple Silicon (~12 GB).
Text-only build (vision tower not included). Runs via MLX Swift / swift-transformers; in Python the Tekken tokenizer needs transformers<5.
Usage
pip install -U mlx-lm
mlx_lm.generate \
--model TyKaoz/Mistral-Small-3.2-24B-Instruct-2506-4bit \
--prompt "Explique la quantization en une phrase." \
--max-tokens 200
| Base | Tool | Precision | Size |
|---|---|---|---|
mistralai/Mistral-Small-3.2-24B-Instruct-2506 |
mlx-lm |
4-bit ยท group 64 | ~12 GB |
By TyKaoz โ privacy-first native macOS LLM chat client. Apache 2.0, inherited from the base model.
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Model size
24B params
Tensor type
BF16
ยท
U32 ยท
Hardware compatibility
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4-bit
Model tree for TyKaoz/Mistral-Small-3.2-24B-Instruct-2506-4bit
Base model
mistralai/Mistral-Small-3.1-24B-Base-2503