---
license: apache-2.0
base_model:
- tokyotech-llm/Qwen3-Swallow-30B-A3B-RL-v0.2
library_name: mlx
tags:
- mlx
- quantized
- apple-silicon
- japanese
- swallow
language:
- ja
- en
pipeline_tag: text-generation
---

# Qwen3-Swallow-30B-A3B-RL-v0.2-MLX-8bit

This model is an [MLX](https://github.com/ml-explore/mlx) format conversion of [`tokyotech-llm/Qwen3-Swallow-30B-A3B-RL-v0.2`](https://huggingface.co/tokyotech-llm/Qwen3-Swallow-30B-A3B-RL-v0.2), optimized for Apple Silicon.

## Model Details

| Attribute | Value |
|---|---|
| **Original Model** | [`tokyotech-llm/Qwen3-Swallow-30B-A3B-RL-v0.2`](https://huggingface.co/tokyotech-llm/Qwen3-Swallow-30B-A3B-RL-v0.2) |
| **Architecture** | Mixture of Experts (MoE) |
| **Parameters** | 30B total / 3B active |
| **Quantization** | 8-bit quantization |
| **Model Size** | ~30 GB |
| **Format** | MLX (Apple Silicon optimized) |
| **Converted with** | mlx-lm v0.30.8 |
| **License** | Apache 2.0 |

## About Qwen3-Swallow

Qwen3-Swallow is a bilingual Japanese-English large language model developed by the [Swallow Project](https://swallow-llm.github.io/) at the Institute of Science Tokyo (formerly Tokyo Institute of Technology) and AIST. Built upon Qwen3 through Continual Pre-Training (CPT), Supervised Fine-Tuning (SFT), and Reinforcement Learning (RL), it achieves strong performance on both Japanese and English tasks while maintaining capabilities in mathematics and coding.

For more details, see the [original model card](https://huggingface.co/tokyotech-llm/Qwen3-Swallow-30B-A3B-RL-v0.2).

## Usage

### Quick Start (Python)

```python
from mlx_lm import load, generate

model, tokenizer = load("tocchitocchi/Qwen3-Swallow-30B-A3B-RL-v0.2-MLX-8bit")

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

response = generate(model, tokenizer, prompt=prompt, verbose=True, max_tokens=512)
```

### Interactive Chat

```bash
mlx_lm.chat --model tocchitocchi/Qwen3-Swallow-30B-A3B-RL-v0.2-MLX-8bit
```

### OpenAI-Compatible Server

```bash
mlx_lm.server --model tocchitocchi/Qwen3-Swallow-30B-A3B-RL-v0.2-MLX-8bit --port 8080
```

Then connect with any OpenAI-compatible client at `http://localhost:8080/v1`.

## Acknowledgments

- Original model by [Swallow Project](https://swallow-llm.github.io/) (Institute of Science Tokyo and AIST)
- MLX framework by [Apple Machine Learning Research](https://github.com/ml-explore/mlx)
- Conversion performed using [mlx-lm](https://github.com/ml-explore/mlx-lm)