prithivMLmods/LensVLM-9B-GGUF

LensVLM-9B-GGUF

LensVLM-9B is a 9-billion-parameter vision-language model from Apple, built on Qwen3.5-9B, introduced in the paper "LensVLM: Selective Context Expansion for Compressed Visual Representation of Text." Its core mechanism scans a compressed image representation of text — at configurable compression ratios of 5x, 10x, or 15x — and then selectively expands only the pages relevant to a given question back to their uncompressed form via learned tools, allowing the model to process very long documents without holding the entire uncompressed text in context. It's run via the accompanying ml-lensvlm codebase with a simple demo script accepting a text file and a question, and is released under the Apple Machine Learning Research Model License (with the accompanying source code separately licensed under the Apple Sample Code License).

Model Files

llama.cpp

LLM inference in C/C++ — https://github.com/ggml-org/llama.cpp