Irfanuruchi/Qwen3-4B-Computer-Science-MLX-4bit

Qwen3-4B-Computer-Science-MLX-4bit

Overview

Qwen3-4B-Computer-Science-MLX-4bit is a 4-bit MLX conversion of Qwen3-4B-Computer-Science for inference on Apple Silicon.

The model was converted from the original BF16 Safetensors release using mlx-lm. It is intended for local inference on supported Mac systems using the MLX framework.

Model Information

Training Data

The source model was instruction-tuned using permissively licensed datasets.

Dataset Size

Intended Use

This model is intended for:

• —Software engineering
• —Programming assistance
• —Code generation
• —Debugging
• —Code review
• —Algorithm implementation
• —Computer science education
• —General technical reasoning

Installation

Install MLX-LM:

python -m pip install mlx-lm

Usage

Command Line

mlx_lm.generate \
  --model Irfanuruchi/Qwen3-4B-Computer-Science-MLX-4bit \
  --prompt "Write a Python function that returns the first n Fibonacci numbers." \
  --max-tokens 200

Python

from mlx_lm import generate, load

model, tokenizer = load(
    "Irfanuruchi/Qwen3-4B-Computer-Science-MLX-4bit"
)

response = generate(
    model,
    tokenizer,
    prompt="Write a Python function that returns the first n Fibonacci numbers.",
    max_tokens=200,
)

print(response)

Conversion

The model was converted from:

Irfanuruchi/Qwen3-4B-Computer-Science

Conversion configuration:

Release Validation

The release was validated locally on Apple Silicon.

Performance measurements are from one local generation test and may vary by device, prompt, context length, and software version.

Release Artifacts

model.safetensors
model.safetensors.index.json
config.json
generation_config.json
tokenizer.json
tokenizer_config.json
added_tokens.json
special_tokens_map.json
merges.txt
vocab.json
README.conversion.md
SHA256SUMS
LICENSE
README.md

Integrity Verification

Verify the downloaded files on macOS:

shasum -a 256 -c SHA256SUMS

On Linux:

sha256sum -c SHA256SUMS

Limitations

• —Quantization can affect output quality relative to the BF16 checkpoint.
• —The model may produce incorrect or incomplete code.
• —Generated code should be reviewed and tested before use.
• —Performance depends on the Apple Silicon device and available memory.
• —This release is intended for MLX-compatible systems.

License

The model is distributed under the Apache License 2.0.

The source model is based on Qwen3-4B, which is also distributed under the Apache License 2.0.

Acknowledgements

• —Alibaba Qwen Team
• —Apple MLX Team
• —Hugging Face
• —SmolTalk contributors
• —DeepCoder contributors

Citation

@software{uruci2026qwen3computersciencemlx,
  title={Qwen3-4B-Computer-Science-MLX-4bit},
  author={Irfan Uruçi},
  year={2026},
  publisher={Hugging Face}
}