> 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.

# Step-3.5

[Step-3.5-Flash](https://huggingface.co/stepfun-ai/Step-3.5-Flash) is a Mixture-of-Experts language model from Stepfun AI, designed for efficient inference.

|                  |                                                 |
| ---------------- | ----------------------------------------------- |
| **Task**         | Text Generation (MoE)                           |
| **Architecture** | `Step3p5ForCausalLM`                            |
| **Parameters**   | varies                                          |
| **HF Org**       | [stepfun-ai](https://huggingface.co/stepfun-ai) |

## Available Models

* **Step-3.5-Flash**

## Architecture

* `Step3p5ForCausalLM`

## Example HF Models

| Model          | HF ID                                                                           |
| -------------- | ------------------------------------------------------------------------------- |
| Step-3.5-Flash | [`stepfun-ai/Step-3.5-Flash`](https://huggingface.co/stepfun-ai/Step-3.5-Flash) |

## Example Recipes

| Recipe                                                                                                                                                    | Description                                                 |
| --------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------- |
| [step\_3.5\_flash\_hellaswag\_pp.yaml](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_finetune/stepfun/step_3.5_flash_hellaswag_pp.yaml) | SFT — Step-3.5-Flash on HellaSwag with pipeline parallelism |

## 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
```

This recipe was validated on **16 nodes × 8 GPUs (128 H100s)**. See the [Launcher Guide](/job-launchers/slurm-cluster) for multi-node setup.

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

```bash
automodel --nproc-per-node=8 examples/llm_finetune/stepfun/step_3.5_flash_hellaswag_pp.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/stepfun/step_3.5_flash_hellaswag_pp.yaml
```

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

## Fine-Tuning

See the [Large MoE Fine-Tuning Guide](/recipes-e2e-examples/large-moe-fine-tuning).

## Hugging Face Model Cards

* [stepfun-ai/Step-3.5-Flash](https://huggingface.co/stepfun-ai/Step-3.5-Flash)