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# mimo-v2.6-distill-qwen-9b-torch

Agentic 9B vision-language model distilled from MiMo-V2.6 onto Qwen3.5 for object detection via 2D grounding.

**Details**

- Model name: `mimo-v2.6-distill-qwen-9b-torch`
- Model source: [https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B](https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B)
- Model author: Xiaomi MiMo
- Model license: MIT
- Model size: 17.56 GB
- Exposes embeddings? no
- Tags: `detection, vlm, torch, transformer, zero-shot`

**Requirements**

- Packages: `torch, torchvision, transformers>=5.12.0, accelerate`
- CPU support
  - yes
- GPU support
  - yes

**Example usage**

```python
import fiftyone as fo
import fiftyone.zoo as foz

dataset = foz.load_zoo_dataset(
    "coco-2017",
    split="validation",
    dataset_name=fo.get_default_dataset_name(),
    max_samples=50,
    shuffle=True,
)

model = foz.load_zoo_model("mimo-v2.6-distill-qwen-9b-torch")

dataset.apply_model(model, label_field="predictions")

session = fo.launch_app(dataset)
```