Modal + Datalab: Deploy high-throughput document intelligence in <5 minutes

What this post added

This post details the deployment of Datalab's Marker and Surya document intelligence models on Modal. It highlights how Modal's platform, specifically its GPU compute capabilities, autoscaling, and caching mechanisms (Modal Volumes), enables high-throughput document processing. The post provides a quickstart guide and explains the underlying technical mechanisms, including environment specification via decorators, GPU usage (e.g., L40s), and the benefits of Modal Volumes for caching model weights. It also quantifies performance gains, showing a 10x throughput increase for Marker on Modal compared to local CPU processing, and discusses how Modal's autoscaling can further improve batch processing throughput.