apple/LensVLM-9B
image-text-to-text model by apple
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Model card & documentation
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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. 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. The source code that accompanies this…
Read the full model card ↗ · Preview checked 2026-09-24T06:37:33.893Z
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Model overview
apple/LensVLM-9B is a image-text-to-text model repository published by apple on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- image-text-to-text
- Library
- transformers
- Recent downloads (30 days)
- 233
- Cumulative likes
- 134
- Hugging Face trending score
- 134
- Reported safetensors parameters
- 9,409,813,744
- Architecture
- Qwen3_5ForConditionalGeneration
- License
- apple-amlr
- Access
- Not gated by Hugging Face
- Created
- 2026-09-21T18:18:20.000Z
- Last modified
- 2026-09-22T21:06:26.000Z
Compatibility and lineage
Language coverage was not reported.
Reported base models: Qwen/Qwen3.5-9B
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-09-24T06:37:30.549Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.