Apple LensVLM-9B
Apple released LensVLM-9B on Sept 24: a 9B vision-language model that scans compressed document-page images and selectively expands only the pages relevant to the question.
Why it matters
Selective-expansion vision for long documents: rather than encoding every page at full resolution, it routes attention to relevant pages, making multi-page document QA tractable on device.
What you could build with it
Pair LensVLM-9B with Sarvam Vision 2.1 in the Launch Radar pipeline: LensVLM selects relevant pages from launch decks, then Sarvam extracts structured metadata.
Does it hold up?
Too early to judge: weights use Apple's Machine Learning Research Model License and code uses Apple's Sample Code License, so check terms before production use.
Built with Apple LensVLM-9B
- apple-aiml-research/ml-lensvlmgithub · 66 ★ · Official Apple AIML Research repo with inference code and docs; created 2026-09-22.
Learn more
GitHub: apple-aiml-research/ml-lensvlm →
First spotted on huggingface: source.
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