AI Engineer · AI

From 15% to 90% GPU Utilization: Fix the Data Pipeline, Not the Model

Your GPUs might be waiting on your data, not your model. This pipeline went from 15% to 90% GPU utilization. Tarun Sunkaraneni from Amazon AGI shows that the hardest part of fast multimodal training often isn't the GPU at all, but keeping it fed with data. Training a Qwen3-VL-style model on images stored in S3, the baseline pipeline spent about 85% of its time waiting on data, mostly loading, decoding and resizing images one at a time. He fixes t

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