# LensVLM 9B

URL: https://interfaze.ai/models/applelensvlm-9b

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LensVLM 9B by apple, a image-text-to-text model with multimodal capabilities. Understand and compare multimodal features, benchmarks, and capabilities.

## Comparison

| Feature | LensVLM 9B | Interfaze |
| --- | --- | --- |
| Input Modalities | text, image | image, text, audio, video, document |
| Native OCR | No | Yes |
| Long Document Processing | No | Yes |
| Language Support | unknown | 162+ |
| Native Speech-to-Text | No | Yes |
| Native Object Detection | No | Yes |
| Guardrail Controls | No | Yes |
| Context Input Size | 32.8K | 1M |
| Tool Calling | Yes | Tool calling supported + built in browser, code execution and web search |

### Scaling

| Feature | LensVLM 9B | Interfaze |
| --- | --- | --- |
| Scaling | Self-hosted/Provider-hosted with quantization | Unlimited |

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View model card on [Hugging Face](https://huggingface.co/apple/LensVLM-9B)

LensVLM is a 9B Vision Language Model (VLM) that scans compressed images of text, then selectively expands only the relevant pages to their uncompressed form via learned tools.

-   Paper: [LensVLM: Selective Context Expansion for Compressed Visual Representation of Text](https://arxiv.org/abs/2605.07019)
-   Code: [https://github.com/apple-aiml-research/ml-lensvlm](https://github.com/apple-aiml-research/ml-lensvlm)

## License

All ML model files in this repository, including Apple's modifications to the Qwen model, are provided under the terms of the [Apple Machine Learning Research Model License](https://huggingface.co/apple/LensVLM-9B/blob/main/LICENSE).

The source code that accompanies this model is distributed separately and is provided under the terms of the Apple Sample Code License.

## Usage

Install the LensVLM code and run inference:

```
git clone https://github.com/apple-aiml-research/ml-lensvlm
cd ml-lensvlm
pip install -r requirements.txt
python scripts/run_demo.py --model apple/LensVLM-9B
```

For a custom document:

```
python demo.py \
    --model apple/LensVLM-9B \
    --text_file document.txt \
    --question "What is the main finding?" \
    --compression 10x
```

Compression options: `5x`, `10x`, `15x`. See the [repository README](https://github.com/apple-aiml-research/ml-lensvlm) for data preparation and evaluation.

## Citation

```
@article{xie2026lensvlm,
  title={LensVLM: Selective Context Expansion for Compressed Visual Representation of Text},
  author={Xie, Roy and Friedman, Dan and Yu, Donghan and Pan, Bowen and Fifty, Christopher and Kim, Jang-Hyun and Du, Xianzhi and Gan, Zhe and Rathod, Vivek and Dhingra, Bhuwan},
  journal={arXiv preprint arXiv:2605.07019},
  year={2026}
}
```

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