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> For a complete documentation index, see https://docs.nvidia.com/nemo/automodel/llms.txt.
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# Kimi-K3

[Kimi-K3](https://huggingface.co/moonshotai/Kimi-K3) is a Moonshot AI vision-language model with a MoonViT3d vision tower and a Kimi Linear Mixture-of-Experts language backbone.

|                   |                                                       |
| ----------------- | ----------------------------------------------------- |
| **Task**          | Image-Text-to-Text / Text Generation                  |
| **Architectures** | `KimiK3ForConditionalGeneration`, `KimiK3ForCausalLM` |
| **HF Org**        | [moonshotai](https://huggingface.co/moonshotai)       |

## Architecture

* `KimiK3ForConditionalGeneration` combines the MoonViT3d vision tower and multimodal projector with the Kimi Linear language backbone.
* `KimiK3ForCausalLM` exposes the text-only Kimi Linear backbone.

## Example HF Models

| Model   | HF ID                                                             |
| ------- | ----------------------------------------------------------------- |
| Kimi-K3 | [`moonshotai/Kimi-K3`](https://huggingface.co/moonshotai/Kimi-K3) |

## Example Recipes

| Recipe                                                                                                                | Dataset   | Description                             |
| --------------------------------------------------------------------------------------------------------------------- | --------- | --------------------------------------- |
| [k3\_hellaswag.yaml](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/llm_finetune/kimi/k3_hellaswag.yaml) | HellaSwag | SFT — text-only Kimi-K3 with EP32 + PP8 |

## Try with NeMo AutoModel

**1. Clone and install from source** ([full instructions](/get-started/installation)):

```bash
git clone https://github.com/NVIDIA-NeMo/Automodel.git
cd Automodel
uv sync --locked --all-groups --all-extras --extra vlm-media
```

**2. Run the text-only recipe** from inside the repo:

```bash
uv run automodel --nproc-per-node=8 examples/llm_finetune/kimi/k3_hellaswag.yaml
```

#### Run with Docker

**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:

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

**3. Run the recipe**:

```bash
automodel --nproc-per-node=8 examples/llm_finetune/kimi/k3_hellaswag.yaml
```

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

## Hugging Face Model Cards

* [moonshotai/Kimi-K3](https://huggingface.co/moonshotai/Kimi-K3)