Llama-3.2-3B-4bit-mlx

Description

This is meta-llama/Llama-3.2-3B converted to MLX format optimized for Apple Silicon (M1/M2/M3) Macs.

• Base Model: meta-llama/Llama-3.2-3B
• Format: MLX
• Quantization: 4bit
• Created with: QuantLLM

Usage

Generate text with mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("codewithdark/Llama-3.2-3B-4bit-mlx")

prompt = "Write a story about Einstein"
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
    messages, add_generation_prompt=True
)

text = generate(model, tokenizer, prompt=prompt, verbose=True)

With streaming

from mlx_lm import load, stream_generate

model, tokenizer = load("codewithdark/Llama-3.2-3B-4bit-mlx")

prompt = "Explain quantum computing"
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
    messages, add_generation_prompt=True
)

for token in stream_generate(model, tokenizer, prompt=prompt, max_tokens=500):
    print(token, end="", flush=True)

Command Line

# Install mlx-lm
pip install mlx-lm

# Generate text
python -m mlx_lm.generate --model codewithdark/Llama-3.2-3B-4bit-mlx --prompt "Hello!"

# Chat mode
python -m mlx_lm.chat --model codewithdark/Llama-3.2-3B-4bit-mlx

Requirements

• Apple Silicon Mac (M1/M2/M3/M4)
• macOS 13.0 or later
• Python 3.10+
• mlx-lm: pip install mlx-lm

Model Details

Property	Value
Base Model	meta-llama/Llama-3.2-3B
Format	MLX
Quantization	4bit
License	apache-2.0
Created	2025-12-19

---

About QuantLLM

This model was converted using QuantLLM - the ultra-fast LLM quantization and export library.

from quantllm import turbo

# Load and quantize any model
model = turbo("meta-llama/Llama-3.2-3B")

# Export to any format
model.export("mlx", quantization="4bit")

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