> 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.

# Moonlight

[Moonlight](https://huggingface.co/moonshotai/Moonlight-16B-A3B) is a Mixture-of-Experts language model from Moonshot AI trained using Muon optimizer. It uses the `DeepseekV3ForCausalLM` architecture with 16B total parameters and 3B activated per token.

|                  |                                                 |
| ---------------- | ----------------------------------------------- |
| **Task**         | Text Generation (MoE)                           |
| **Architecture** | `DeepseekV3ForCausalLM`                         |
| **Parameters**   | 16B total / 3B active                           |
| **HF Org**       | [moonshotai](https://huggingface.co/moonshotai) |

## Available Models

* **Moonlight-16B-A3B**: 16B total, 3B activated

## Architecture

* `DeepseekV3ForCausalLM` (same architecture as DeepSeek-V3)

## Example HF Models

| Model             | HF ID                                                                                 |
| ----------------- | ------------------------------------------------------------------------------------- |
| Moonlight 16B A3B | [`moonshotai/Moonlight-16B-A3B`](https://huggingface.co/moonshotai/Moonlight-16B-A3B) |

## Example Recipes

| Recipe                                                                                                                                                                | Description                                 |
| --------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------- |
| [moonlight\_16b\_te.yaml](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_finetune/moonlight/moonlight_16b_te.yaml)                                   | SFT — Moonlight 16B with Transformer Engine |
| [moonlight\_16b\_te\_packed\_sequence.yaml](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_finetune/moonlight/moonlight_16b_te_packed_sequence.yaml) | SFT — Moonlight 16B with packed sequences   |

## 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/moonlight/moonlight_16b_te.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/moonlight/moonlight_16b_te.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).

## Hugging Face Model Cards

* [moonshotai/Moonlight-16B-A3B](https://huggingface.co/moonshotai/Moonlight-16B-A3B)