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# Qwen3.5-122B-A10B

> Use NeMo AutoModel to fine-tune Qwen3.5-122B-A10B for VLM workflows with checked-in image-text-to-text recipes and documented distributed settings.

[Qwen3.5-122B-A10B](https://huggingface.co/Qwen/Qwen3.5-122B-A10B) has a checked-in NeMo AutoModel recipe for image-text-to-text.
The Hugging Face configuration declares the `Qwen3_5MoeForConditionalGeneration` architecture.

## Fine-Tune Qwen3.5-122B-A10B

Follow the [installation instructions](/get-started/installation), then review the checked-in recipe and
its declared topology below before choosing a local or cluster launcher.

Use the [Slurm launcher guide](/job-launchers/slurm-cluster) for the multi-node run.

## Choose a Workflow

| Goal                                  | Start Here                                                                                                                                           |
| ------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------- |
| Run the primary recipe for this model | Use the [recipe configuration](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/vlm_finetune/qwen3_5_moe/qwen3_5_122b_128k_ep8cp32.yaml). |
| Prepare your environment              | Follow the [installation instructions](/get-started/installation).                                                                                   |

### Configuration

| Setting  | Configuration                                                                             |
| -------- | ----------------------------------------------------------------------------------------- |
| Hardware | -                                                                                         |
| Strategy | FSDP2; tp\_size=1, pp\_size=1, cp\_size=32, ep\_size=8                                    |
| Nodes    | 16                                                                                        |
| Features | Activation checkpointing (activation\_checkpointing=true), HybridEP (dispatcher=hybridep) |
| Advanced | torch.bfloat16, attention=sdpa, linear=torch, experts=torch\_mm, dispatcher=hybridep      |

## Model Reference

### Model Architecture

| Property     | Value                                |
| ------------ | ------------------------------------ |
| Task         | Image-text-to-text                   |
| Architecture | `Qwen3_5MoeForConditionalGeneration` |

### Available Models

* [`Qwen/Qwen3.5-122B-A10B`](https://huggingface.co/Qwen/Qwen3.5-122B-A10B)

## Related Resources

* [Vision-language model fine-tuning guide](/recipes-e2e-examples/gemma-3-3n)