Enable 3.5 times faster vision language models with quantization

This blog post discusses the advancements in quantized vision-language models (VLMs), showcasing how reduced precision versions of models like Pixtral and Qwen2 can achieve significantly faster inference speeds (up to 3.5 times) while maintaining high accuracy. It details various deployment scenarios, benchmarks, and the implications of quantization on model performance across different GPU architectures. The piece highlights the importance of these developments for efficient AI deployment and offers links to open-source resources for further exploration.