> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/nemo/automodel/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo/automodel/_mcp/server.

# Qwen3

[Qwen3](https://qwenlm.github.io/blog/qwen3/) is Alibaba Cloud's third-generation dense language model series, featuring improved reasoning, instruction following, and multilingual capabilities over Qwen2.

|                  |                                     |
| ---------------- | ----------------------------------- |
| **Task**         | Text Generation                     |
| **Architecture** | `Qwen3ForCausalLM`                  |
| **Parameters**   | 0.6B – 32B                          |
| **HF Org**       | [Qwen](https://huggingface.co/Qwen) |

## Available Models

* **Qwen3**: 0.6B, 1.7B, 4B, 8B, 14B, 32B

## Architecture

* `Qwen3ForCausalLM`

## Example HF Models

| Model      | HF ID                                                       |
| ---------- | ----------------------------------------------------------- |
| Qwen3 0.6B | [`Qwen/Qwen3-0.6B`](https://huggingface.co/Qwen/Qwen3-0.6B) |
| Qwen3 8B   | [`Qwen/Qwen3-8B`](https://huggingface.co/Qwen/Qwen3-8B)     |
| Qwen3 32B  | [`Qwen/Qwen3-32B`](https://huggingface.co/Qwen/Qwen3-32B)   |

## Example Recipes

| Recipe                                                                                                                                  | Description                     |
| --------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------- |
| [qwen3\_0p6b\_hellaswag.yaml](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_finetune/qwen/qwen3_0p6b_hellaswag.yaml)  | SFT — Qwen3 0.6B on HellaSwag   |
| [qwen3\_8b\_squad\_spark.yaml](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_finetune/qwen/qwen3_8b_squad_spark.yaml) | SFT — Qwen3 8B on SQuAD (Spark) |

## Try with NeMo AutoModel

**1. Install** ([full instructions](/get-started/installation)):

```bash
pip install nemo-automodel
```

**2. Clone the repo** to get the example recipes:

```bash
git clone https://github.com/NVIDIA-NeMo/Automodel.git
cd Automodel
```

**3. Run the recipe** from inside the repo:

```bash
automodel --nproc-per-node=8 examples/llm_finetune/qwen/qwen3_0p6b_hellaswag.yaml
```

**1. Pull the container** and mount a checkpoint directory:

```bash
docker run --gpus all -it --rm \
  --shm-size=8g \
  -v $(pwd)/checkpoints:/opt/Automodel/checkpoints \
  nvcr.io/nvidia/nemo-automodel:26.06.00
```

**2.** Navigate to the AutoModel directory (where the recipes are):

```bash
cd /opt/Automodel
```

**3. Run the recipe**:

```bash
automodel --nproc-per-node=8 examples/llm_finetune/qwen/qwen3_0p6b_hellaswag.yaml
```

See the [Installation Guide](/get-started/installation) and [LLM Fine-Tuning Guide](/recipes-e2e-examples/sft-peft).

## Fine-Tuning

See the [LLM Fine-Tuning Guide](/recipes-e2e-examples/sft-peft) for full SFT and LoRA instructions.

## Hugging Face Model Cards

* [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B)
* [Qwen/Qwen3-32B](https://huggingface.co/Qwen/Qwen3-32B)