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Jeevan Bhoot

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#computer vision Preprint Aug 2026

Llama-Mobile: Efficient 2.7-Bit Quantization of VLMs

This work presents a framework for quantizing VLMs for efficient inference on resource-constrained hardware, which combines a quantization pipeline that uses the model itself to generate training data and does not require access to the training setup, with a novel 2.7-bit-per-parameter format.

Luka Ribar, Jeevan Bhoot, Douglas Orr · 0 citations